The initial stage of statistical research. Types of averages

The result of the first stage of statistical research - statistical observation - is information characterizing each unit of the statistical population. However, the ability to reflect the patterns and trends in the dynamics of the phenomena under study with the help of even the most complete characterization of individual facts is limited. Such data is obtained only as a result of a statistical summary. A summary is an ordering, systematization and generalization of statistical data obtained during statistical observation. Only proper processing of statistical material makes it possible to reveal the essence of socio-economic phenomena, the characteristic features and essential features of individual types, to discover patterns and trends in their development. A distinction is made between a simple and a group summary, or a summary in a narrow and broad sense. A simple summary is the calculation of the totals in groups and subgroups and the presentation of this material in tables. As a result of a simple summary of statistical data, it is possible to determine the number of enterprises, the total number of employees, the volume of production in monetary terms. These summaries are for the most part informative. They give a generalized characteristic of the population in the form of absolute values.

A group summary, or a summary in the broad sense, is a complex process for the multilateral processing of primary statistical data, i.e. data obtained as a result of observation. It includes the grouping of statistical data, the development of a system of indicators to characterize groups, the calculation of group and overall results, the calculation of general indicators. The task of the statistical summary as the second stage of statistical research is to obtain generalizing indicators for information, reference and analytical purposes. The summary of mass statistical data is carried out according to a previously developed program and plan. In the process of developing the program, the subject and predicate of the summary are determined. The subject is the object of study, divided into groups and subgroups. The predicate is indicators that characterize the subject of the summary. The summary program is determined by the objectives of the statistical study.

Statistical summary is carried out according to a predetermined plan. The summary plan addresses questions about how to work on summarizing information - manually or mechanically, about the sequence of individual summary operations. The deadlines for the completion of each stage and the summary as a whole, as well as the methods for presenting the results of the summary, are established. These can be distribution series, statistical tables and statistical graphs.

received materials.

summary indicators.

Each observation is carried out with a specific purpose. When conducting it, it is necessary to establish what is to be examined. The following questions need to be addressed:

Object of observation

Unit of observation

Qualification

sign

The observation program is drawn up in the form of forms (questionnaires, forms), in which primary data are entered. A necessary addition to the forms is an instruction that explains the meaning of the questions.

terms of observation;

preparatory work;

For example, the critical moment of the micro-census of 1994. was 0.00 am on the night of February 13-14. By establishing the critical moment of observation, one can determine the true state of affairs with photographic accuracy.

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Stages of statistical research. Collected during the first stage of statistical research - statistical observation - data on the value of any feature of the studied population

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Collected during the first stage of the statistical study - statistical observation - data on the value of any feature of the studied population should be processed in such a way that an accurate and detailed answer to all the questions posed by the purpose of the study is obtained. The task of the second stage of statistical research is statistical processing (summaries) - consists in ordering and generalizing the primary material, bringing it into groups and, on this basis, giving a generalized description of the totality. The quality of the initial statistical material predetermines the quality of the generalizing indicators obtained as a result of the statistical summary.

Distinguish summary simple and complex (statistical grouping).

Simple Summary is an operation to calculate the totals for a set of units of observation. Complex summary - this is a set of operations that includes grouping observation units, counting the totals for each group and for the entire population, and presenting the results of the summary and grouping in the form of statistical tables.

Statistical grouping is reduced to the division of the population into groups according to to the selected feature essential for the units of the population (grouping feature ). The choice of a grouping feature, i.e. sign , according to which the units of the studied population are united into groups, - one of the most significant and complex issues in the theory of grouping and statistical research . The results of the entire statistical study often depend on the correct choice of a grouping attribute.

Statistical observation. Stages of statistical research

Grouping makes it possible to obtain such results by which it is possible to identify the composition of the population, the characteristic features and properties of typical phenomena, to discover patterns and relationships.

The simplest and most commonly used way of summarizing statistical data is distribution ranks . The statistical series (law) of distribution is the numerical distribution of units of the population according to the trait under study. Let some SW be discrete, i.e. can only take fixed (on some scale) values X i . In this case, a series of probabilities P(X i) for all ( i=1, 2, …, n) admissible values of this quantity is called its distribution law.

Depending on the grouping feature used, statistical series can be attributive and variational (quantitative).

Attribute rows distributions reflect the qualitative state of the units of the population (person's gender, marital status, sectoral affiliation of the enterprise, its form of ownership, etc.), and variational - have a numerical expression (production volume, family income, age of a person, academic score, etc.).

An example of an attribute series is the distribution of students in a group by gender.

Variational (quantitative) grouped series can be discrete or interval . A discrete variational distribution series is a series in which the numerical distribution of population units according to a discrete attribute is expressed as an integer finite value. An example is the distribution of workers by category, the distribution of city families by the number of children, and so on. An interval distribution series is a series in which the characteristic values are given as an interval. The construction of interval variation series is expedient, first of all, for random variables characterized by a continuous variation of a feature (i.e., when the value of a feature in population units can take on any values, even if within certain limits).

So, the probability distribution law of a discrete SW carries all the information about it. This law (or simply the distribution of a random variable) can be specified in three ways:

— in the form of a table of quantity values and their corresponding probabilities;

- in the form of a diagram or, as it is sometimes called, a distribution histogram;

- in the form of a formula, for example, for normal, binomial, etc. distribution.

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Stages of statistical research

Stages of statistical research.

Statistical study- this is a collection, summary and analysis of data (facts) on socio-economic, demographic and other phenomena and processes of public life in the state, scientifically organized according to a single program, with registration of their most significant features in accounting documentation.

Distinctive features (specifics) of statistical research are: purposefulness, organization, mass character, consistency (complexity), comparability, documentation, controllability, practicality.

Statistical research consists of three main stages:

1) collection of primary statistical information(statistical observation) - observation, collection of data on the values of the studied attribute of units of statistical cos-ty, kt is the foundation of future statistical analysis. If a mistake was made during the collection of primary statistical data or the material turned out to be of poor quality, this will affect the correctness and reliability of both theoretical and practical conclusions.

2) statistical summary and processing of primary information- Data is organized and grouped. The results of statistical grouping and summaries are presented in the form of statistical tables, which is the most rational, systematized, compact and visual form of presenting mass data.

3) generalization and interpretation of statistical information- analysis of statistical information.

All these stages are interconnected, the absence of one of them leads to a break in the integrity of the statistical study.

Stages of stat research

1. Goal setting

2. Definition of the object of observation

3. Definition of units of observation

4. Drawing up a research program

5. Drawing up instructions for filling out the form

6. Summary and grouping of data (brief analysis)

Basic concepts and categories of statistical science.

1. Statistical population- a set of phenomena that have one or more common features and differ from each other in the values of other features. Such, for example, are the totality of households, the totality of families, the totality of enterprises, firms, associations, etc.

2. Sign - this property, a characteristic feature of the phenomenon, subject to statistical study

3. Statistical indicator- this is a generalizing quantitative characteristic of the social economy of phenomena and processes in their qualitative certainty in the conditions of a particular place and time. Statistical indicators can be divided into two main types: accounting and estimated indicators (sizes, volumes, levels of the phenomenon under study) and analytical indicators (relative and average values, variation indicators, etc.).

4. Unit of owls- this is each individual, subject to statistical study.

5. Variation- this is the variability of the magnitude of the attribute in individual units of co-phenomena.

6. Regularity- called the repetition and order of change in phenomena.

The main stages of statistical observation.

St-some observation is a scientifically based collection of data on the social economy phenomenon of social life.

CH stages:

1. Preparation for statistical observation - involves the use of the method of mass observations, which is nothing more than the collection of primary statistical information. (solution of scientific, methodological and organizational and technical issues).

2. Summary and grouping of primary stats- the collected information is summarized and distributed in a certain way using the method of stat groupings. including work, begins with the distribution of census sheets, questionnaires, forms, statistical reporting forms and ends with their submission after filling in to the bodies conducting the observation.

3. Analysis of statistical information- using the method of generalizing indicators, the analysis of statistical information is carried out.

4. Development of proposals for improving the CH- analyzes the reasons that led to the incorrect filling of statistical forms and develops proposals for improving the observation.

Obtaining information during CT SN requires a considerable amount of financial labor and time. (opinion polls)

Grouping statistics.

grouping- this is the division of owls into groups according to essential features.

Reasons for grouping: the originality of the object of the statistical study.

The grouping method solves the following problem: allocation of socio-economy types and phenomena; study of the structure of the phenomenon and structural changes occurring in it; revealing the relationship and dependence between phenomena.

These tasks are solved with the help of typological, structural and analytical groupings.

Typological group– identification of types of social-economic phenomena (group of industrial enterprises by form of ownership)

Structural group– study of structure and structural shifts. With the help of such groups, the following can be studied: the composition of us-I by gender, age, place of residence, etc.

Analytical group- identifying the relationship between features.

Stages of building SG:

1.selection of a grouping feature

2.determination of the required number of groups, into kt it is necessary to divide the studied owl

3. set the boundaries of the gr-ki intervals

4. setting for each group of indicators or their system, which should characterize the selected groups.

grouping systems.

Grouping system- this is a series of interrelated statistical groupings according to the most significant features, comprehensively reflecting the most important aspects of the phenomena under study.

Typological group- this is the division of the studied qualitatively heterogeneous society into classes, social-economy types (group of industrial enterprises by form of ownership)

Structural group- characterizes the composition of a homogeneous cos-ty according to certain characteristics. With the help of such groups, the following can be studied: the composition of us-I by gender, age, place of residence, etc.

Analytical group- used in the study of the relationship between features, one of the kt is factorial (influences the change in performance), the other is productive (features that change under the influence of factors).

Construction and types of distribution series.

Stat number of distribution- this is an ordered distribution of units of owls into groups according to a certain varying trait.

Distinguish: attributive and variational happy distributions.

Attributive- these are r.r., built on qualitative grounds. R.r. taken in the form of tables. They characterize the composition of the owls according to the existing features, taken over several periods, these data allow us to study the change in the structure.

variational are r.r. built on a quantitative basis. Any variation series consists of 2 elements: variants and frequencies.

Options individual values of the attribute are considered, which it takes in the variation series, i.e.

specific value of the variable attribute.

Frequencies- this is the number of individual options or each group of the variation series, i.e. these are numbers showing how often certain variants occur in the r.r.

Variation series:

1.discrete- characterizes the distribution of units of owls on a discrete basis (the distribution of families according to the number of rooms in individual apartments).

2.interval– the feature is presented as an interval; it is expedient first of all at a continuous variation of a sign.

The most convenient r.r. analyze with the help of their graphical representation, which makes it possible to judge the form of distribution. A visual representation of the nature of the change in the frequencies of the variational series is given by a polygon and a histogram, there is an ogive and a cumulate.

Statistical tables.

ST is a rational and common form of presenting statistical data.

The table is the most rational, visual and compact form of presentation of statistical material.

The main techniques that determine the technique for the formation of ST trace:

1. T should be compact and contain only those initial data that directly reflect the studied socio-economy phenomenon in the article.

2. The heading of the table and the names of the columns and lines should be clear and concise.

3.inf-tion is located in the columns (columns) of the table, ends with a summary line.

5. it is useful to number columns and lines, etc.

According to the logical content, STs are a “stat sentence”, the main elements being the subject and the predicate.

Subject the name of the object, characterized by numbers. this is m.b. one or more owls, otd units of owls.

Predicate ST are indicators that characterize the object of study, i.e. subject of the table. The predicate is the top headings and the state of the content column from left to right.

9. The concept of absolute value in statistics .

Stat pok-whether is a qualitatively defined variable that quantitatively characterizes the object of study or its properties.

A.v.- this is a generalizing indicator that characterizes the size, scale or volume of a particular phenomenon in specific conditions of place and time.

Ways of expression: natural units (t., pcs., quantity); labor dimension (slave. Wr, labour); value expression

How to get: registration of facts, summary and grouping, calculation according to defined methodology (GDP, ratings, etc.)

Types of AB: 1.individual AB - characterize individual elements of general phenomena 2. Total AB - har-t indicators for co-objects.

Absolute change (/_\) is the difference between 2 AB.

Stages and methods of statistical research

Statistical research consists of three main stages:

Statistical observation is the first stage. In the course of it, primary statistical information and data are collected, which will become the basis for future statistical analysis. Statistical observation methods are represented by censuses, statistical reporting, questioning, and selective observation.

Statistical summary is the second stage. In the course of it, the processing of primary information takes place; specific single information is generalized, forming a set in order to identify typical features and patterns inherent in the phenomenon under study as a whole. The main method of statistical summary is grouping, when the studied phenomena are divided into the most important types, characteristic groups and subgroups according to essential features. The results of the statistical grouping and summaries are presented in the form of tables and graphs.

Generalization and analysis of statistical information is the third stage. Statistical analysis is the final stage of statistical research.

The main stages of the analysis are the following:

1. establishing the facts and their assessment;

2. establishing the characteristic features and causes of the phenomenon;

3. comparison of the phenomenon with the basic phenomena - normative, planned and others;

4. formulation of hypotheses, conclusions and assumptions;

5. statistical verification of the hypotheses put forward with the help of special generalizing statistical indicators.

General indicators- absolute, relative, average values and index systems - are used at this stage. The general features of the formation of generalizing indicators are established by measuring their deviations and bringing them to an average indicator. The study of deviations - "variations" - together with the use of average and relative values is of great practical and scientific importance. Indicators of deviations of "variations" characterize the degree of homogeneity of the statistical population according to the desired attribute. Indicators of "variations" determine the degree and boundaries of variation. Of considerable interest is the relationship of signs of "variations".

All these three stages are inextricably linked by an organic unity. Thus, statistical observation is meaningless without further analysis, and analysis is impossible without information obtained at the stage of primary data processing.

The processing of empirical research data is usually divided into several stages:

1) Primary data processing:

- Compilation of tables;

— Transformation of the form of information;

- Data validation.

2) Statistical data analysis:

— Analysis of primary statistics;

— Evaluation of the reliability of differences;

— Data normalization;

— Correlation analysis;

- Factor analysis.

In most cases, it is advisable to start data processing with the compilation of pivot tables.

Pivot data table- this is a kind of "accumulator" of all the data obtained as a result of the study, ideally it should contain the data of all subjects according to all research methods. Pivot tables are usually compiled in Microsoft Office Excel, or Word, Access.

The basis for the pivot table of the source data is the following form. Each line contains the values of all indicators of one subject. Each column (field) contains the values of one indicator for all subjects. Thus, in each cell (cell) of the table, only one value of one indicator of one subject is recorded. The topmost line contains the subject's number in order, full name (or some other identifier), measured indicators, scale ratings, etc. This line makes it easier to navigate the table. In each subsequent line, the name of the subject and the values of all parameters measured from him are recorded; of course, for all subjects in the same order of indicators.

The subjects can be listed in alphabetical order, but it is better to use this principle at the lowest level of division. First, it is better to divide the subjects according to their belonging to any subgroups that will be compared with each other. Within these subgroups, it is useful to sort the subjects by gender, age, or another parameter that is important to you.

Transformation of the form of information.

It is advisable to enter all the signs of interest to you in the table in the form of a decimal number, that is, pre-calculate minutes into decimal fractions of an hour, seconds into decimal fractions of a minute, the number of months into a decimal fraction of a year, etc. This is necessary because the data format for most computer programs in use today imposes its own limitations. Also, try not to enter various text characters (periods, commas, dashes, etc.) into the table without special need.

All information that can be encoded by numbers is better converted into numerical form. This will give more opportunities for different types of data processing. The exception is the first line, which contains the names (more often short names - abbreviations) of the measured indicators. In the form of numbers in the table, you can also enter information about those sample parameters that may presumably be significant factors, but you have in qualitative terms.

Methods and main stages of statistical research

The simplest operations can be: numerical coding (men - 1, women - 2; trained - 1, not passed - 2, etc.) and the conversion of qualitative indicators into ranks.

Data validation.

After creating a table on paper or computer, it is necessary to check the quality of the received data. To do this, it is often enough to carefully examine the data array. You should start checking by identifying errors (typos), which consist in the fact that the order of the number is written incorrectly. For example, 100 is written instead of 10, 9.4 is written instead of 94, etc. If you look closely at the columns, this is easy to detect, since parameters that vary greatly are relatively rare. Most often, the values of one parameter have the same order or nearest orders. When collecting data on a computer, it is important to comply with the requirements for the data format in the statistical program used. First of all, this applies to the sign, which must separate the integer part from the fractional part in the decimal number (dot or comma).

The use of methods of mathematical statistics in the processing of primary empirical data is necessary to increase the reliability of the conclusions of a scientific study. At the same time, it is not recommended to limit the use of indicators such as arithmetic averages and percentages. They most often do not provide sufficient grounds for reasonable conclusions from empirical data.

The choice of the method of statistical analysis of the obtained empirical data is a very important and responsible part of the study. And it's better to do it before the data is received. When planning a study, it is necessary to think in advance which empirical indicators will be recorded, by what methods they will be processed, and what conclusions can be drawn with different processing results.

When choosing a statistical criterion it is necessary, first of all, to identify the type of variables (features) and the scale of measurement that was used when measuring indicators and other variables - for example, age, family composition, level of education. Variables can be any indicators that can be compared with each other (that is, measured). It should be borne in mind that nominative and ordinal scales can be widely used in studies: verbal and non-verbal behavioral responses, gender, level of education - all this can be considered as variables. The main thing is to have clear and precise criteria for assigning them to one type or another, depending on the hypotheses and tasks set.

When choosing a statistical criterion, one should also focus on the type of data distribution that was obtained in the study. Parametric tests are used when the distribution of the received data is considered to be normal. A normal distribution is more likely (but not necessarily) to be obtained with samples of more than 100 subjects (it may work with fewer, or it may not work with more). When using parametric criteria, it is necessary to check the normality of the distribution.

For nonparametric criteria, the type of data distribution does not matter. With small sample sizes of subjects, it is advisable to choose nonparametric criteria that give greater confidence in the conclusions, regardless of whether the study obtained a normal distribution of data. In some cases, statistically valid conclusions can be drawn even with samples of 5-10 subjects.

Many studies look for differences in measured indicators among subjects with certain characteristics. When processing relevant data, criteria can be used to identify differences in the level of the trait under study or in its distribution. To determine the significance of differences in the manifestation of a trait in studies, indicators such as the paired Wilcoxon test, the Mann-Whitney U-test, the x-square (x2) test, Fisher's exact test, and the binomial test are often used.

In many studies, the search for the relationship of the studied indicators in the same subjects is carried out. Correlation coefficients can be used to process the relevant data. The relationship of values with each other and their dependence is often characterized by Pearson's linear correlation coefficient and Spearman's rank correlation coefficient.

The data structure (and, accordingly, the structure of the studied reality), as well as their relationship, is revealed by factor analysis.

In many studies, it is of interest to analyze the variability of a trait under the influence of any controlled factors, or, in other words, to assess the influence of various factors on the studied trait. For mathematical data processing in such problems, the Mann-Whitney U-test, the Kruskal-Wallis test, the Wilcoxon T-test, the ? 2 Friedman. However, to study the influence, and even more so the mutual influence of several factors on the parameter under study, analysis of variance may be more useful. The researcher proceeds from the assumption that some variables can be considered as causes, and others as consequences. Variables of the first kind are considered factors, while variables of the second kind are considered to be effective features. This is the difference between analysis of variance and correlation analysis, in which it is assumed that changes in one attribute are simply associated with certain changes in another.

In many studies, the significance of changes (shift) of any parameters and manifestations over a certain period of time, under certain conditions (for example, under conditions of corrective action) is revealed. Formative experiments in practical psychology solve precisely this problem. To process the relevant data, coefficients can be used to assess the reliability of the shift in the values of the trait under study. For this, sign criteria, the Wilcoxon T-test, are often used.

It is important to pay attention to the limitations that each criterion has. If one criterion is not suitable for the analysis of the available data, it is always possible to find some other one, perhaps by changing the type of presentation of the data itself. Before statistical analysis of empirical data, it is useful to check whether there are cut-offs corresponding to the amount and type of data you have. Otherwise, you may be disappointed when your calculations turn out to be in vain due to the absence of critical values in the table with the sample size that you had.

After getting acquainted with the procedure for calculating the criterion, you can carry out "manual" data processing or use the statistical program of a personal computer.

For computer processing, the most popular programs are SPSS and Statistica.

The use of statistical programs in computer processing speeds up the processing of the material by several orders of magnitude and provides the researcher with such methods of analysis that cannot be implemented in manual processing. However, these advantages can be fully utilized if the researcher has the necessary level of training in this area. Usually, the more powerful a computer program (the more powerful it is), the more time it takes to master. Thus, spending time studying it with rare access to a powerful statistical apparatus is not entirely effective. Very often, the use of such programs to solve even simple tasks also requires a certain amount of skills.

In order to avoid unnecessary difficulties and time costs, it is much more effective to turn to professionals. They will qualitatively and professionally carry out all the necessary mathematical and statistical analysis of your research data: analysis of primary statistics, assessment of the reliability of differences, data normalization, correlation and factor analysis, etc.

After carrying out the necessary statistical analysis of the data, it is necessary to correlate the results obtained with the initially posed hypothesis, with the theoretical justifications of the authors who have studied this topic and previous researchers. Formulate conclusions and interpret the results.

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Main stages of statistical research

Consider the most important method of statistics - statistical observation.

Using various methods and techniques of statistical methodology

requires the availability of comprehensive and reliable information about the studied

object. The study of mass social phenomena includes the stages of collecting

statistical information and its primary processing, information and grouping

observation results in certain aggregates, generalization and analysis

received materials.

At the first stage of statistical research, primary

statistical data, or raw statistical information that

is the foundation of the future statistical building. For the building to be

solid, solid and high-quality should be its basis. If when collecting

primary statistical data, an error was made or the material turned out to be

poor quality, it will affect the correctness and reliability of both

theoretical as well as practical findings. Therefore, statistical

observation from the initial to the final stage - obtaining the final

materials - should be carefully thought out and clearly organized.

Statistical observation provides the source material for generalization, the beginning

which serves as a summary. If during statistical observation about each of its

unit receive information that characterizes it from many sides, then the data

summaries characterize the entire statistical population and its individual parts.

At this stage, the population is divided according to the signs of difference and combined according to

signs of similarity, total indicators are calculated for groups and in

in general. Using the grouping method, the studied phenomena are divided into the most important

types, characteristic groups and subgroups according to essential features. Via

groupings are limited qualitatively homogeneous in a significant respect

totality, which is a prerequisite for the definition and application

summary indicators.

At the final stage of the analysis with the help of generalizing indicators

relative and average values are calculated, a summary assessment is given

variations of signs, the dynamics of phenomena is characterized, indices are applied,

balance constructions, indicators are calculated that characterize the tightness

connections in the change of signs. For the most rational and clear

presentation of digital material, it is presented in the form of tables and graphs.

3. Statistical observation: concept, basic forms.

This is a scientific and organizational work to collect data. Forms: stat. 1) reporting, cat. based on documentary accounting. since 1998, 4 unified forms of federal state supervision have been introduced: FP-1 (project issue), FP-2 (investment), FP-3 (financial state of organizations), FP-4 (number of -t workers, labor), 2) specially organized observation (census), 3) a register is a s-ma pok-lei, which characterizes each unit of observation: registers of us- niya, pr-ty, construction sites and contractors. org-tions, retail and wholesale trade. Types of observation: 1) continuous, non-continuous (selective, qualified based on the main array method, monograph). Observation is current, period., One-time. Observation methods: direct, documentary, survey (forwarding agent, questionnaire, private, correspondence). Statistical observations are carried out according to the plan, which includes: program-methodological issues (goals, tasks), organizational issues (time, place). As a result of the observations, errors occur, the cat reduces the accuracy of the observations, therefore, data control is carried out (logical and counting). As a result of checking the authentic data, the following observation errors are revealed: random. errors (registration errors), intentional errors, unintentional (system. and non-system.), errors of representativeness (representativeness).

Program-methodological issues of statistical observation.

Program and methodological issues of statistical observation

Each observation is carried out with a specific purpose.

When conducting it, it is necessary to establish what is to be examined. The following questions need to be addressed:

Object of observation - a set of objects, phenomena, from which information should be collected. When defining an object, its main distinguishing features (features) are indicated. Any object of mass observations consists of their individual units, so it is necessary to decide what is the element of the totality that will serve as the unit of observation.

Unit of observation - this is an integral element of the object, which is the carrier of signs subject to registration and the basis of the account.

Qualification are certain quantitative restrictions for the object of observation.

sign - this is a property that characterizes certain features and characteristics inherent in the units of the studied population.

Organizational issues of statistical observation.

The observation program is drawn up in the form of forms (questionnaires, forms), in which primary data are entered.

A necessary addition to the forms is an instruction that explains the meaning of the questions.

The organizational issues of the program include:

terms of observation;

critical moment of observation;

preparatory work;

The period of observation to which the recorded information is referred. It is called the objective observation time. This might be a certain period of time (day, decade, month) or a certain moment. The moment to which the recorded information relates is called the critical moment of observation.

For example, the critical moment of the micro-census of 1994. was 0.00 h.

on the night of February 13-14. By establishing the critical moment of observation, one can determine the true state of affairs with photographic accuracy.

Preparatory work provides for the provision of observation with documents, as well as the compilation of a list of reporting units, forms, instructions.

Documents m. will be filled in during the observation or based on its results.

An important place in the system of preparatory work is the selection and training of personnel, as well as the briefing of those who will participate in the observation.

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Stages of statistical research.

Stage 1: Statistical observation.

Stage 2: Reduction and grouping of the results of observation into certain populations.

Stage 3: Generalization and analysis of the received materials. Identification of interrelations and scales of phenomena, determination of patterns of their development, development of predictive estimates. It is important to have comprehensive and reliable information about the object under study.

At the first stage of statistical research, primary statistical data, or initial statistical information, is formed, which is the foundation of the future statistical "building".

STAGES OF STATISTICAL RESEARCH

In order for the “building” to be durable, solid and of high quality, its foundation must be. If an error was made in the collection of primary statistical data or the material turned out to be of poor quality, this will affect the correctness and reliability of both theoretical and practical conclusions. Therefore, statistical observation from the initial to the final stage must be carefully thought out and clearly organized.

Statistical observation provides the source material for generalization, the beginning of which is summary. If, during statistical observation, information is obtained about each of its units that characterizes it from many sides, then these reports characterize the entire statistical aggregate and its individual parts. At this stage, the population is divided according to the signs of difference and combined according to the signs of similarity, the total indicators are calculated for the groups and as a whole. Using the grouping method, the studied phenomena are divided into the most important types, characteristic groups and subgroups according to essential features. With the help of groupings, qualitatively homogeneous populations are limited, which is a prerequisite for the definition and application of generalizing indicators.

At the final stage of the analysis, with the help of generalizing indicators, relative and average values are calculated, an assessment of the variation of signs is given, the dynamics of phenomena is characterized, indices and balance constructions are applied, indicators are calculated that characterize the closeness of relationships in changing signs. For the purpose of the most rational and visual presentation of digital material, it is presented in the form of tables and graphs.

The cognitive value of statistics thing is:

1) statistics provides a digital and meaningful coverage of the phenomena and processes under study, serves as the most reliable way to assess reality; 2) statistics gives probative force to economic conclusions, allows you to check various "walking" statements, individual theoretical positions; 3) statistics has the ability to reveal the relationship between phenomena, to show their form and strength.

1. STATISTICAL OBSERVATION

1.1. Basic concepts

Statistical observation — this is the first stage of statistical research, which is a scientifically organized accounting of facts characterizing the phenomena and processes of social life, and the collection of data obtained on the basis of this accounting, scientifically organized according to a single program.

However, not every collection of information is a statistical observation. One can talk about statistical observation only when statistical regularities are studied, i.e. those that manifest themselves in a mass process, in a large number of units of some set. Therefore, statistical observation should be planned, massive and systematic.

Plannedness statistical observation lies in the fact that it is prepared and carried out according to a developed plan, which includes questions of methodology, organization, collection of information, quality control of the collected material, its reliability, and presentation of the final results.

Mass the nature of statistical observation suggests that it covers a large number of cases of manifestation of this process, sufficient to obtain truthful data characterizing not only individual units, but the entire population as a whole.

Systematic statistical observation is determined by the fact that it must be carried out either systematically, or continuously, or regularly.

The following requirements are imposed on statistical observation:

1) completeness of statistical data (completeness of coverage of units of the studied population, aspects of a particular phenomenon, as well as completeness of coverage over time);

2) reliability and accuracy of data;

3) their uniformity and comparability.

Any statistical research must begin with the formulation of its goals and objectives. After that, the object and unit of observation are determined, a program is developed, and the type and method of observation are selected.

Object of observation- a set of socio-economic phenomena and processes that are subject to research, or the exact boundaries within which statistical information will be recorded . For example, during a population census, it is necessary to establish what kind of population is subject to registration - cash, that is, actually located in a given area at the time of the census, or permanent, that is, permanently living in a given area. When surveying industry, it is necessary to establish which enterprises will be classified as industrial. In some cases, one or another qualification is used to limit the object of observation. Qualification- a restrictive feature that all units of the studied population must satisfy. So, for example, during the census of production equipment, it is necessary to determine what is attributed to production equipment, and what to hand tools, which equipment is subject to the census - only operating or also under repair, in stock, reserve.

Unit of observation is called an integral part of the object of observation, which serves as the basis for counting and has features that are subject to registration during observation.

So, for example, in a population census, the unit of observation is each individual person. If the task is also set to determine the number and composition of households, then each household will be the unit of observation along with a person.

Observation Program- this is a list of issues on which information is collected, or a list of signs and indicators to be registered . The observation program is drawn up in the form of a form (questionnaire, form), in which primary information is entered. A necessary addition to the form is an instruction (or indications on the forms themselves), explaining the meaning of the question. The composition and content of the questions of the observation program depend on the objectives of the study and on the characteristics of the social phenomenon being studied.

The concept of studying the quantitative aspects of objects and phenomena was formed long ago, from the moment a person developed elementary skills in working with information. However, the term "statistics", which has come down to our time, was borrowed much later from the Latin language and comes from the word "status", which means "a certain state of things." “Status” was also used in the meaning of “political state” and was fixed in almost all European languages in this semantic meaning: English “state”, German “Staat”, Italian “stato” and its derivative “statista” - a connoisseur of the state.

The word “statistics” was widely used in the 18th century and was used in the meaning of “state science”. Statistics is a branch of practical activity aimed at collecting, processing, analyzing and providing public use of data on the phenomena and processes of social life.

Analysis is a method of scientific research of an object by considering its individual aspects and components.

Economic-statistical analysis is the development of a methodology based on the widespread use of traditional statistical and mathematical-statistical methods in order to control the adequate reflection of the phenomena and processes under study.

Stages of statistical research. Statistical research takes place in three stages:

1) statistical observation;
2) summary of received data;
3) statistical analysis.

At the first stage, using the method of mass observations, primary statistical data are collected.

At the second stage of the statistical study, the collected data are subjected to primary processing, summary and grouping. The grouping method allows you to select homogeneous populations, divide them into groups and subgroups. Summary - this is the receipt of totals for the population as a whole and its individual groups and subgroups.

The results of grouping and summary are presented in the form of statistical tables. The main content of this stage is the transition from the characteristics of each unit of observation to the summary characteristics of the population as a whole or its groups.

At the third stage, the obtained summary data are analyzed by the method of generalizing indicators (absolute, relative and average values, variation indicators, index systems, methods of mathematical statistics, tabular method, graphical method, etc.).

Fundamentals of statistical analysis:

1) assertion of facts and establishment of their assessment;
2) identification of characteristic features and causes of the phenomenon;
3) comparison of the phenomenon with normative, planned and other phenomena, which are taken as the basis for comparison;
4) formulation of conclusions, forecasts, assumptions and hypotheses;
5) statistical verification of the proposed assumptions (hypotheses).

Analysis and generalization of statistical data is the final stage of statistical research, the ultimate goal of which is to obtain theoretical conclusions and practical conclusions about the trends and patterns of the studied socio-economic phenomena and processes. The tasks of statistical analysis are: determination and evaluation of the specifics and features of the phenomena and processes under study, the study of their structure, interrelations and patterns of their development.

Statistical analysis of data is carried out in close connection with the theoretical, qualitative analysis of the essence of the phenomena under study and the corresponding quantitative tools, the study of their structure, relationships and dynamics.

Statistical analysis is a study of the characteristic features of the structure, connection of phenomena, trends, patterns of development of socio-economic phenomena, for which specific economic-statistical and mathematical-statistical methods are used. Statistical analysis is completed by the interpretation of the obtained results.

In statistical analysis, signs are divided according to the nature of their influence on each other:

1. Sign-result - the sign analyzed in this study. The individual dimensions of such a feature in individual elements of the population are influenced by one or more other features. In other words, the attribute-result is considered as a consequence of the interaction of other factors;
2. Sign-factor - a sign that influences the studied sign (feature-result). Moreover, the relationship between the sign-factor and the sign-result can be quantitatively determined. Synonyms of this term in statistics are "factor sign", "factor". It is necessary to distinguish between the concepts of a sign-factor and a sign-weight. A sign-weight is a sign that must be taken into account in the calculations. But, the sign-weight does not affect the studied sign. A feature-factor can be considered as a feature-weight, i.e., taken into account in the calculations, but not every feature-weight is a feature-factor. For example, when studying in a group of students the relationship between the time of preparing for an exam and the number of points obtained in the exam, the third attribute should also be taken into account: "The number of people certified for a certain score." The last feature is not influencing the result, however, will be included in the analytical calculations. It is this trait that is called the weight trait, and not the factor trait.

Before proceeding with the analysis, it is necessary to check whether the conditions that ensure its reliability and correctness are met:

- Reliability of primary digital data;
- Completeness of coverage of the studied population;
- Comparability of indicators (accounting units, territory, calculation method).

The main concepts of statistical analysis are:

1. Hypothesis;
2. Decisive function and decisive rule;
3. Sample from the general population;
4. Assessment of the characteristics of the general population;
5. Confidence interval;
6. trend;
7. Statistical relationship.

Analysis is the final stage of statistical research, the essence of which is the identification of relationships and patterns of the phenomenon under study, the formulation of conclusions and proposals.

The intensification of the work of medical workers in the conditions of budgetary insurance health care imposes increased requirements on scientific and organizational factors. Under these conditions, the role of medical statistics in the scientific and practical activities of a medical institution is increasing.

In practical and research activities, a doctor, as a rule, analyzes the results of his activity not only at the individual, but also at the group and population levels. This is necessary for the doctor to confirm the level of qualification, as well as for further improvement and professional specialization. Therefore, the ability to properly organize and conduct a statistical study is necessary for all doctors of various profiles, heads of institutions and health authorities. Such knowledge and skills contribute to improving the quality and efficiency of medical care to the population through continuous training of personnel (the most important element of resource provision) and, thus, the competitiveness of medical institutions of various forms of ownership in a market economy.

Healthcare leaders constantly use statistical data in operational and prognostic work. Only a qualified analysis of statistical data, assessment of events and appropriate conclusions make it possible to make the right managerial decision, contribute to better organization of work, more accurate planning and forecasting. Statistics help to control the activities of the institution, to manage it promptly, to judge the quality and effectiveness of treatment and preventive work. When drawing up current and long-term work plans, the leader should be based on the study and analysis of trends and patterns in the development of both health care and the health status of the population of his district, city, region, etc.

The traditional statistical system in health care is based on the receipt of data in the form of reports, which are compiled in grass-roots institutions and then summarized at intermediate and higher levels. The reporting system has not only advantages (a single program, ensuring comparability, indicators of the amount of work and use of resources, simplicity and low cost of collecting materials), but also certain disadvantages (low efficiency, rigidity, inflexible program, a limited set of information, uncontrolled accounting errors, etc. .).

Analysis of the work done should be carried out by doctors not only on the basis of existing reporting documentation, but also through specially conducted selective statistical studies.

The plan of statistical research is drawn up in accordance with the planned program. The main points of the plan are:

determination of the purpose of the study;
determination of the object of observation;
determination of the period of work at all stages;
indication of the type of statistical observation and method;
determination of the place where observations will be made;
finding out by what forces and under whose methodological and organizational leadership the research will be carried out.

The organization of statistical research is divided into several stages:

the stage of acquaintance with the literature data, which allows you to get an idea about the problem under study, choose an adequate research methodology and formulate a working hypothesis
observation stage;
statistical grouping and summary;
counting processing;
scientific analysis;
literary and graphic design of the research data.

The program of statistical research provides for the solution of the following questions:

determination of the unit of observation and drawing up a program for collecting material;
Unit of observation- each primary element of the statistical population.
The unit of observation is endowed with signs of similarity and difference, which are subject to accounting and further observation, therefore these signs are called taken into account (accounting).
Considered features- signs by which the elements of the unit of observation in the statistical population differ. Signs are classified:
- by nature to:
  a) attributive (descriptive) signs - expressed verbally;
  b) quantitative characteristics - expressed as a number;
- by role in total on:
  a) factor signs that affect the phenomenon under study;
  b) effective features that change under the influence of factor features.
Example: in our study, the unit of observation is a student studying at a given medical school for all years. Considered signs by nature are divided into:
a) attributive - gender, bad habits, health status, etc.;
b) quantitative - age, number of cigarettes smoked, duration of illness, smoking experience, etc.;
c) according to the totality of factor signs - the presence of bad habits and smoking experience;
d) effective signs - the state of health, the presence of a disease, etc.
The material collection program is a consistent statement of the signs taken into account - questions that need to be answered when conducting this study. This may be a specially compiled by the researcher questionnaire, questionnaire, map. The document must have a clear title. Questions (signs taken into account) should be clear, concise, consistent with the purpose and objectives of the study; Each question should have a choice of answers. These ready-made answers are called "grouping".
The grouping of features is carried out in order to single out homogeneous groups for the study of certain patterns of the phenomenon under study. The grouping of responses according to attributive characteristics is called typological, according to quantitative characteristics - variational.
An example of a typological grouping:
- grouping of students by gender:
  - the male,
  - female;
- grouping students by the presence or absence of bad habits:
  - smoking students,
  - non-smoking students.
Variation grouping example:
- grouping students by the number of cigarettes smoked per day:
  - 10 or less;
  - over 20
An example of a map completed by a medical student in a study of smoking prevalence is shown below. All map questions have groupings and recommendations for filling it out.
Map* on the study of the prevalence of smoking among medical students
1. Full name of the student ____________________________ (fill in completely)
2. Course: I, II, III, IV, V, VI
3. Faculty: medical, medical and preventive, pharmaceutical, faculty of military training
4. Age: under 20, 20, 21, 22, 23, 24, 25 and over
5. Gender: male/female
6. Do you recognize that smoking is injurious to health? Yes, no, I don't know
7. Who smokes from people living with you: father, mother, brother, sister, husband, wife, comrade, no one smokes
8. Do you smoke? Well no
9. Age at which the first cigarette was smoked: under 15 years old, 16-18 years old, over 18 years old
10. How many cigarettes (cigarettes) do you smoke per day? 5-10, 11-20, more than 20
11. What prompted you to smoke for the first time: the example of your parents, the example of your teachers, the influence of your comrades, the desire to look like an adult, the desire to lose weight, curiosity, the desire to keep up with fashion?
And other questions in accordance with the purpose and objective of the study.

drawing up a material development program; The program for developing the obtained data provides for the compilation of layouts of statistical tables, taking into account groupings.

Requirements for tables. Layouts of statistical tables should have a clear and concise title corresponding to their content. The table distinguishes between subject and predicate.

The statistical subject is what the table says. The tabular subject contains the main features that are the subject of research, and is usually placed on the left side of the table vertically.

The statistical predicate is what characterizes the subject and is placed horizontally.

It is necessary to provide for the final data in the tables, according to which the calculations of indicators will be carried out at the third stage of the statistical study when processing the received data.

Types of tables. Statistical tables are divided into simple, group, combination.

Simple (Table 1) is a table that allows you to analyze the received data, grouped by only one attribute (subject).

Table 1. Distribution of smoking students by faculties (in absolute numbers and in % of the total)

Group (Table 2) is called a table in which a relationship is established between individual features, i.e. in addition to the subject, there is a predicate represented by one or more groupings that are related (in pairs) to the subject groupings, but are not related to each other.

Table 2. Distribution of students of various faculties by sex and age at which they smoked their first cigarette

combinational (Table 3) is called a table in which there are two or more predicates that are connected not only with the subject, but also with each other.

Table 3. Distribution of smoking students of various faculties by sex and the average number of cigarettes (cigarettes) smoked per day

Name of faculties

Average number of cigarettes (cigarettes) smoked by students per day

Total

10 or less

11 - 20

over 20

well

both sexes

well

both sexes

well

both sexes

well

both sexes

1. Medical

2. Medico-prophylactic

3. Pharmaceutical, etc.

Total:

drawing up a program for analyzing the collected material.
The analysis program provides a list of statistical methods necessary to identify the patterns of the phenomenon under study.
The research plan provides for the solution of the following organizational issues:
1. The choice of the object of study
2. Determination of the size of the statistical population
3. Terms and place (territory) of the study, types and methods of observation and collection of material
4. Characteristics of performers (personnel)
5. Characteristics of technical equipment and required material resources
6. The object of statistical research is the totality from which the necessary information will be collected. This may be the population, students, patients, hospitalized in hospitals, etc.
Population - a group consisting of relatively homogeneous elements, taken together within known boundaries of time and space in accordance with the goal. The structure of the statistical population: the statistical population consists of units of observation (see diagram).
On the example of our study, the statistical population is students studying at a given university throughout the entire period of study.
There are two types of population - general and sample.
Population - this is a group consisting of all relatively homogeneous elements in accordance with the goal.
Sample population - a part of the general population selected for research and intended to characterize the entire general population. It should be representative (representative) in quantity and quality in relation to the general population.
Representativeness quantitative is based on the law of large numbers and means a sufficient number of elements of the sample, calculated using special formulas and tables.
Representativeness is qualitative is based on the law of probability and means the correspondence (uniformity) of the signs characterizing the elements of the sample in relation to the general one.
In our example, the general population is all medical students; sample set - part of the students of each course and faculty of a given university.
The volume of the statistical population is the number of elements of the population taken for the study.
Dates and place (territory) of the study - this is the preparation of a calendar plan for the implementation of this study at a given stage in a specific area. Example: from April 1 to June 1 of the current year in the MMA. THEM. Sechenov.
Types of observation :
1. current (or permanent) observation - when registration is carried out continuously as units of observation appear. Example: each case of birth, death, treatment in medical institutions.
2. and one-time (or one-time) observation - when the phenomena being studied are fixed at a certain moment (hour, day of the week, date). Example: population census, composition of hospital beds.
Research methods. It is important for the researcher to determine the method of conducting the study: continuous observation or non-continuous (selective).
1. Continuous observation is the registration of all units of observation that make up the general population.
2. Non-continuous (selective) observation - the study of only a part of the population to characterize the whole.
Methods for conducting research on a sample population (monographic, main array, questionnaire, etc.).
1. The monographic method is used in the study of any one object, when one of the many objects is selected and studied with maximum completeness in order to show best practices, to identify trends in the development of the phenomenon. Example: description of a new surgical technology.
2. The main array method is used in the study of those objects in which the majority of the studied phenomena are concentrated. Its essence lies in the fact that from all the units of observation that are part of a given object, their main part is selected, which characterizes the entire statistical population. Example: A factory has 7 main workshops employing 1300 workers and two small auxiliary workshops employing 100 workers. For observation, you can take only the main workshops and draw conclusions from them regarding the entire plant.
3. The questionnaire method is used to collect statistical information using specially designed questionnaires. Example: when studying the prevalence of gastrointestinal diseases among students of vocational schools in the city of N., a questionnaire was developed with a list of questions of interest to the researcher.

Methods for the selection of the studied phenomena and the formation of a sample population

There are the following methods of selection of the studied phenomena: random, mechanical, nested, directed, typological.

Random selection is a selection carried out by lot (by the initial letter of the surname or by birthday, etc.).
Mechanical selection is a selection when every fifth (20%) or tenth (10%) unit of observation is mechanically selected from the entire population.
Nested (serial) selection - when not individual units are selected from the general population, but nests (series), which are selected by random or mechanical sampling. Example: to study the incidence of the rural population of the M-sky region, the incidence of the rural population of one, the most typical point, is being studied. The results apply to the entire rural population of the region.
Directed selection is a selection when only those units of observation are selected from the general population in order to identify certain patterns, which will reveal the influence of unknown factors while eliminating the influence of known ones. Example: when studying the influence of work experience on injuries, workers of the same profession, of the same age, of the same workshop, of the same educational level are selected.
Typological selection is the selection of units from pre-grouped similar qualitative groups. Example: when studying the patterns of mortality among the urban population, the studied cities should be grouped according to the population in them.

Characteristics of performers (personnel) . How many people and what qualifications conduct the study. Example: a study on the study of the sanitary and hygienic regime of students of senior classes of secondary schools of the district is carried out by two doctors and two assistants to the sanitary doctor of the hygiene and epidemiology center of this administrative district.

Characteristics of technical equipment and required material resources :

laboratory equipment and devices corresponding to the purpose of the study;
stationery (paper, forms);
without additional funds.

The collection of material is the process of registration, filling in officially existing or specially designed accounting documents (coupons, cards, etc.). The collection of material is carried out according to the previously compiled program and research plan. The 3rd stage of the statistical study includes the following actions sequentially performed by the researcher:

control of the collected material - this is a check of the collected material in order to select accounting documents that have defects for their subsequent correction, addition or exclusion from the study. For example, the questionnaire does not indicate gender, age, or there are no answers to other questions posed. In this case, additional accounting documents (outpatient cards, medical histories, etc.) are required. If these data cannot be obtained from additional records brought in by the researcher, then low-quality maps (questionnaires) should be excluded from the study.
encryption - this is the use of symbols for distinguished features. When manually processing the material, ciphers can be digital, alphabetic; at machine - only digital.
Example: letter encryption:
Floor:
husband. M
female F
digital encryption:
material grouping - this is the distribution of the collected material according to an attributive or quantitative attribute (typological or variational). Example: grouping of students according to the courses of study: I course, II course, III course, IV course, V course, VI course.
summary of data in statistical tables - entering the digital data obtained after counting into tables
calculation of statistical indicators and statistical processing of the material .

Purpose of the study: to develop measures to reduce diseases of the digestive system (BOP) among medical students.

Research objectives:

To study the prevalence of various diseases of the digestive system (BOP) among medical students.
Determine the risk factors for the occurrence of BOP.
Develop proposals for the university administration

Research program:

The unit of observation is a student with a diagnosis of BOP, studying at a medical university at this faculty.
Attributive features: gender, diagnosis, diet.
Quantitative signs: age, duration of illness, interval between meals, number of meals per day.
Effective signs: the presence of a disease of the digestive system.
Factor signs: gender, age, nature of nutrition, etc.

Material collection program (questionnaire completed by the student)

a) full name
b) Course: 1,2,3,4,5,6
c) Faculty: medical (1), medical and preventive (2), pharmaceutical (3)
d) Age: up to 20 years old inclusive - (1), 21-22 - (2), 23-24 - (3), 25 and over (4)
e) Gender: male (1), female (2)
f) How many times a day do you eat? One - (1), two - (2), three or more (3)
g) Meal consists of sandwiches without tea (1), sandwiches with tea (2), full meal (3), other (4) (specify)
__________________________
h) What is the interval between meals: up to 1 hour (1), 1-2 hours (2), 3-4 hours (3), 5 hours or more (4)
i) Does the class schedule include time for lunch: (yes - (1), no - (2)
j) Do you have a disease of the digestive system: yes - (1), no - (2)
k) If you answered "yes", then indicate the diagnosis: ___________________
l) Duration of the disease: up to 1 year - (1), 2-3 years - (2), 4-5 years - (3), 6 years or more - (4)

And other questions in accordance with the purpose and objectives of the study.

Material Development Program
Typological grouping: grouping students by faculties, gender, by disease diagnosis.
Variation grouping: grouping according to the duration of the disease (up to 1 year, 2-3 years, 4-5 years, 6 years or more), the interval between meals (up to 1 hour, 1-2 hours, 3-4 hours, 5 hours and more).

Statistical table layouts

simple table
Table 4. Distribution of students with diseases of the digestive system by nosological forms (in % of the total)

group table
Table 5. Distribution of students with diseases of the digestive system by sex and age (in % of the total)

Disease	Floor		Age			Total
Disease	husband	wives	up to 15 years	15 - 18 years old	over 18 years old	Total
1. Gastritis
2. Peptic ulcer of the stomach
3. Peptic ulcer of the duodenum 12
4. Others
Total:

combination table
Table 6. Distribution of students with diseases of the digestive system, by faculties and sex (in % of the total)

Disease

Therapeutic

Medico-prophylactic

Pharmaceutical

Total

well

both sexes

well

both sexes

well

both sexes

well

both sexes

1. Gastritis

2. Peptic ulcer of the stomach

3. Peptic ulcer of the 12th duodenal ulcer

4. Others

Total:

Study plan

The object of the study is a student of a medical university studying at a given medical university at a given faculty.
The size of the statistical population: a sufficient number of observations. Population: sample, representative in quality and quantity.
Terms of the study: February 6 - June 6 of the current year.
Methods of collecting material: questionnaires, copying from the medical documents of the student clinic.

Vlasov V.V. Epidemiology. - M.: GEOTAR-MED, 2004. - 464 p.
Lisitsyn Yu.P. Public health and healthcare. Textbook for high schools. - M.: GEOTAR-MED, 2007. - 512 p.
Medik V.A., Yuriev V.K. A course of lectures on public health and health care: Part 1. Public health. - M.: Medicine, 2003. - 368 p.
Minyaev V.A., Vishnyakov N.I. and others. Social medicine and healthcare organization (Guide in 2 volumes). - St. Petersburg, 1998. -528 p.
Kucherenko V.Z., Agarkov N.M. and others. Social hygiene and organization of health care (Tutorial) - Moscow, 2000. - 432 p.
S. Glantz. Medico-biological statistics. Per from English. - M., Practice, 1998. - 459 p.

To get an idea about a particular phenomenon, to draw conclusions, it is necessary to conduct a statistical study. The subject of statistical research in health care and medicine can be the health of the population, the organization of medical care, various sections of the activities of medical institutions, environmental factors that affect the state of health.

The methodical sequence of performing a statistical study consists of certain stages.

Stage 1. Drawing up a plan and program of research.

Stage 2. Collection of material (statistical observation).

Stage 3. Material development, statistical grouping and summary

Stage 4. Statistical analysis of the phenomenon under study, formulation of conclusions.

Stage 5 Literary processing and presentation of the results.

Upon completion of the statistical study, recommendations and management decisions are developed, the results of the study are put into practice, and efficiency is evaluated.

In conducting a statistical study, the most important element is the observance of a strict sequence in the implementation of these stages.

First stage statistical research - drawing up a plan and program - is preparatory, at which the purpose and objectives of the study are determined, a plan and research program are drawn up, a program for summarizing statistical material is developed and organizational issues are resolved.

When starting a statistical study, it is necessary to accurately and clearly formulate the purpose and objectives of the study, to study the literature on this topic.

The goal determines the main direction of research and is, as a rule, not only theoretical, but also practical. The goal is formulated clearly, clearly, unambiguously.

To disclose the goal, the research tasks are defined.

An important aspect of the preparatory phase is the development of an organizational plan. The organizational plan of the study provides for the definition of the place (administrative-territorial boundaries of the observation), time (specific terms for the implementation of the observation, development and analysis of the material) and the subject of the study (organizers, performers, methodological and organizational leadership, research funding sources).

Pl a n research d ov a nia includes:

Definition of the object of study (statistical population);

The scope of the study (continuous, non-continuous);

Types (current, one-time);

Ways to collect statistical information. Research program includes:

Definition of the unit of observation;

List of questions (accounting signs) to be registered in relation to each unit of observation*

Development of an individual accounting (registration) form with a list of questions and features to be recorded;

Development of table layouts, in which the results of the study are then entered.

For each unit of observation, a separate form is filled out, it contains a passport part, clearly formulated questions of the program, put in a certain sequence, and the date of filling out the document.

As accounting forms, accounting medical forms used in the practice of medical institutions can be used.

Other medical documents (case histories, and individual cards of an outpatient, the history of the development of the child, the history of childbirth), reporting forms of medical institutions, etc. can serve as sources of information.

To enable the statistical development of data from these documents, the information is copied onto specially designed accounting forms, the content of which is determined in each individual case in accordance with the objectives of the study.

At present, in connection with the machine processing of the results of observation using a computer, program questions can be formalized , when questions in the accounting document are put in the form of alternatives (yes, no) , or ready-made answers are offered, from which a specific answer should be selected.

At the first stage of the statistical study, along with the observation program, a program * of the summary of the data obtained is compiled, which includes the establishment of the principles of grouping, the selection of grouping characteristics , determination of combinations of these signs, drawing up layouts of statistical tables.

Second phase- collection of statistical material (statistical observation) - consists in the registration of individual cases of the phenomenon under study and the accounting signs characterizing them in registration forms. Before and during the performance of this work, instruction (oral or written) of the observers is carried out, and they are provided with registration forms.

In terms of time, statistical observation can be current and one-time.

At current observation Yu denia the phenomenon is studied for some separate period of time (week, quarter , year, etc.) by daily recording of the phenomenon as each case occurs. An example of a current observation is accounting for the number of births , dead, sick , discharged from the hospital, etc. This takes into account rapidly changing phenomena.

At one-time observation Yu denia statistical data are collected at a certain (critical) point in time. One-time observations are: a population census, a study of the physical development of children, accounting for hospital beds for horses of the year, certification of medical institutions, etc. Preventive examinations of the population also belong to this type. One-time registration reflects the state of the phenomenon at the time of study. This type of observation is used to study slowly changing phenomena.

The choice of the type of observation over time is determined by the purpose and objectives of the study. For example, the characteristics of hospitalized patients can be obtained as a result of the current registration of those who left the hospital (current observation) or by a one-day census of patients in the hospital (one-time observation).

Depending on the completeness of the coverage of the phenomenon under study, a continuous and non-continuous study is distinguished.

At continuous The study studies all the units of observation included in the population, i.e. the general population. A continuous study is carried out in order to establish the absolute size of the phenomenon, for example, the total population, the total number of births or deaths, the total number of cases of a particular disease, etc. The continuous method is also used in cases where information is necessary for operational work (accounting for infectious diseases , workload of doctors, etc.)

At discontinuous The study examines only part of the general population. It is divided into several types: questionnaire, monographic, main array, selective. The most common method in medical research is the sampling method.

Monographic method- gives a detailed description of individual units of the population, characteristic in any respect, and a deep, comprehensive description of objects.

Main Array Method- involves the study of those objects in which the vast majority of units of observation are concentrated. The disadvantage of this method is that a part of the population remains uncovered by the study, although small in size, but which can differ significantly from the main array.

Questionnaire method- this is the collection of statistical data using specially designed questionnaires addressed to a certain circle of people. This study is based on the principle of voluntariness, so the return of questionnaires is often incomplete. Often the answers to the questions posed bear the imprint of subjectivity and chance. This method is used to obtain an approximate description of the phenomenon under study.

Sampling method- is reduced to the study of some specially selected part of the units of observation to characterize the entire general population. This method has the advantage of obtaining results with a high degree of reliability as well as a significantly lower cost. The study employs a smaller number of performers , moreover, it requires less time.

In medical statistics, the role and place of the sampling method is especially great, since medical workers usually deal with only a part of the phenomenon under study: they study a group of patients with a particular disease, analyze the work of individual departments and medical institutions , evaluate the quality of certain events, etc.

According to the method of obtaining information in the course of statistical observation and the nature of its implementation, several types are distinguished:

1) direct observation(clinical examination of patients , conducting laboratory , instrumental research , anthropometric measurements, etc.)

2) sociological methods: interview method (face-to-face survey), questioning (correspondence survey - anonymous or non-anonymous), etc .;

3) documentary research a nie(copy of information from accounting and reporting medical documents, information from official statistics of institutions and organizations.)

Third stage- grouping and summary of material - begins with checking and clarifying the number of observations , completeness and correctness of the information received , identifying and eliminating errors, duplicate records, etc.

For the correct development of the material, encryption of primary accounting documents is used. , those. designation of each feature and its group with a sign - alphabetic or numeric. Encryption is a technique , facilitating and accelerating material development , improving the quality, accuracy of development. Ciphers - symbols - are developed arbitrarily. When coding diagnoses, it is recommended to use the international nomenclature and classification of diseases; when coding professions - a dictionary of professions.

The advantage of encryption is that, if necessary, after the end of the main development, you can return to the material for development in order to clarify new relationships and dependencies. Encrypted accounting material makes it easier and faster , than unencrypted. After checking, the features are grouped.

grouping- division of the totality of the studied data into homogeneous , typical groups according to the most significant features. Grouping can be carried out on qualitative and quantitative grounds. The choice of a grouping feature depends on the nature of the studied population and the objectives of the study.

Typological grouping is carried out according to qualitative (descriptive, attributive) features, for example, by gender , profession, disease groups, severity of the course of the disease, postoperative complications, etc.

Grouping by quantitative (variation) features is carried out on the basis of the numerical size of the feature , For example , by age , the duration of the disease, the duration of treatment, etc. Quantitative grouping requires a solution to the question of the size of the grouping interval: the interval can be equal, and in some cases - unequal, even include the so-called open groups.

for example , when grouping by age, open groups can be determined: up to 1 year . 50 years and older.

When determining the number of groups proceed from the purpose and objectives of the study. It is necessary that groupings could reveal the patterns of the phenomenon under study. A large number of groups can lead to excessive crushing of the material, unnecessary detailing. A small number of groups leads to obscuring of characteristic features.

Having finished grouping the material, proceed to the summary.

With vodka- generalization of isolated cases , obtained as a result of a statistical study, into certain groups, their calculation and inclusion in the layout tables.

A summary of the statistical material is carried out using statistical tables. Table , not filled with numbers , called a layout.

Statistical tables are list , chronological, territorial.

The table has a subject and a predicate. The statistical subject is usually placed on horizontal lines on the left side of the table and reflects the main, main feature. The statistical predicate is placed from left to right along the vertical columns and reflects additional accounting features.

Statistical tables are divided into simple , group and combination.

AT simple tables the numerical distribution of the material according to one attribute is presented , its constituent parts (Table 1). A simple table usually contains a simple list or summary of the totality of the phenomenon under study.

Table 1

Distribution of the dead in the N. hospital by age

AT group tables presents a combination of two signs in connection with each other (Table 2).

table 2

Distribution of the dead in N. hospital by sex and age

AT combin a qi about these tables the distribution of the material according to three or more interrelated features is given (Table 3).

Table 3

Distribution of deaths in N. hospital with different diseases by age and sex

Diagnosis of the underlying disease	Age
0-14	15-19	20-39	40-59	60 and >	Total
m	well	m	well	m	well	m	well	m	well	m	well	m+f
Diseases of the circulatory system.	-	-	-	-
Injury and poisoning		-		-					-
malignancy. neoplasms.	-	-	-	-	-	-
Other zab.	-	-	-	-
Everyone got sick.		-		-

When compiling tables, certain requirements must be met:

Each table should have a heading that reflects its content;

Within the table, all columns should also have clear, concise titles;

When filling out the table, all cells of the table must contain the corresponding numerical data. The cells of the table remaining blank due to the absence of this combination are crossed out ("-"), and in the absence of information in the cell, "n.s." or "...";

After filling the table in the bottom horizontal row and in the last vertical column on the right, the results of vertical columns and horizontal lines are summed up.

Tables must have a single sequential numbering.

In studies with a small number of observations, summarization is done manually. All accounting documents are decomposed into groups in accordance with the sign code. Next, the data is calculated and recorded in the corresponding cell of the table.

Currently, computers are widely used in sorting and summarizing material. . which allow not only to sort the material according to the studied characteristics , but do the calculations.

Fourth stage- statistical analysis - is a crucial stage of the study. At this stage, the calculation of statistical indicators (frequency , structures , the average size of the phenomenon under study), their graphic representation is given , dynamics , trends, connections between phenomena are established . forecasts are given, etc. The analysis involves the interpretation of the data obtained, the assessment of the reliability of the results of the study. In conclusion, conclusions are drawn.

Fifth stage- Literary processing is final. It involves the finalization of the results of a statistical study. The results can be presented in the form of an article, report, report , dissertations, etc. There are certain requirements for each type of design , which must be observed in the literary processing of the results of a statistical study.

The results of medical and statistical research are being introduced into healthcare practice. Various options for using the results of the study are possible: familiarization with the results of a wide audience of medical and scientific workers; preparation of instructive and methodological documents; formulation of a rationalization proposal and others.

STATISTICAL VALUES

For a comparative analysis of statistical data, statistical values are used: absolute , relative , medium.

Absolute values

The absolute values obtained in the summary tables during the statistical study reflect the absolute size of the phenomenon (number of health care facilities, number of hospital beds, population , the number of deaths, births, illnesses, etc.). A number of statistical studies ends with obtaining absolute values. In some cases, they can be used to analyze the phenomenon under study. , For example , when studying rare phenomena , if necessary, know the exact absolute size of the phenomenon , if necessary, pay attention to individual cases of the phenomenon under study, etc. With a small number of observations , in the case when it is not required to determine the regularity , absolute numbers can also be used.

In a significant proportion of cases, absolute values cannot be used for comparison with data from other studies. For this, relative and average values are used.

Relative values

Relative values (indicators , coefficients) are obtained as a result of the ratio of one absolute value to another. The most commonly used indicators are: , extensive, ratios , visibility.

Intensive- frequency indicators , intensity, prevalence of the phenomenon in the environment , producing this phenomenon. In health care, morbidity is being studied , mortality , disability, birth rate and other indicators of population health. Wednesday , in which the processes take place is the population as a whole or its individual groups (age, gender, social , professional, etc.). In medical-statistical studies, a phenomenon is, as it were, a product of the environment. for example , population (environment) and sick (phenomenon); sick (environment) and dead (phenomenon), etc.

The value of the base is selected in accordance with the value of the indicator - by 100, 1000, 10000, 100000, depending on this, the indicator is expressed as a percentage , ppm , prodecimille, prosantimille.

The intensive indicator is calculated as follows: for example, in Iran in 1995. 67283 thousand inhabitants lived, 380200 people died during the year.

Intensive indicators can be general and special.

General intensive indicators characterize the phenomenon as a whole . For example , total fertility rates , mortality, morbidity, calculated for the entire population of the administrative territory.

Special intensive indicators (by group) are used to characterize the frequency of the phenomenon in different groups (morbidity by sex, age , mortality among children under 1 year of age , lethality for individual nosological Forms, etc.).

Intensive indicators are used: to determine the level . frequencies , prevalence of the phenomenon; to compare the frequency of the phenomenon in two different populations; for learning changes in the frequency of the phenomenon in dynamics.

extensive- indicators of specific gravity, structure, characterize the distribution of the phenomenon into its constituent parts, its internal structure. Extensive indicators are calculated by the ratio of the part of the phenomenon to the whole and are expressed in percentages or fractions of a unit.

The extensive indicator is calculated as follows: for example, in Greece in 1997 there were 719 hospitals, including 214 general hospitals.

Extensive indicators are used to determine the structure of the phenomenon and a comparative assessment of the ratio of its constituent parts. Extensive indicators are always interconnected, since their sum is always equal to 100 percent: for example, when studying the structure of morbidity, the proportion of an individual disease may increase with its true growth; at the same level, if the number of other diseases has decreased; with a decrease in the number of this disease , if the decrease in the number of other diseases occurs at a faster rate.

Ratios- represent the ratio of two independent, independent of each other , qualitatively different values. Correlation indicators include indicators of the provision of the population with doctors, paramedical workers, hospital beds, etc.

The ratio is calculated as follows: for example, in Lebanon, with a population of 3,789 thousand inhabitants, 3,941 doctors worked in medical institutions in 1996.

visibility- are used for the purpose of a more visual and accessible comparison of statistical values. Visualization metrics provide a convenient way to convert absolute, relative, or average values into an easy-to-compare Form. When calculating these indicators, one of the compared values is equated to 100 (or 1), and the remaining values are recalculated accordingly to this number.

The visibility indicators are calculated as follows: for example, the population of Jordan was: in 1994. - 4275 thousand people, in 1995 - 4440 thousand people , in 1996 - 5439 thousand people.

Visibility indicator: 1994-100%;

1995	=	4460 *100	=	103.9%;


1996	=	5439*100	=	127.2%

The visibility indicators indicate by how many percent or how many times there was an increase or decrease in the compared values. Visual indicators are most often used to compare data over time , to present the patterns of the phenomenon under study in a more visual form.

When using relative values, some errors can be made. Here are the most common ones:

1. Sometimes a change in the frequency of a phenomenon is judged on the basis of extensive indicators that characterize the structure of the phenomenon, and not its intensity.

3. When calculating special indicators, you should choose the right denominator for calculating the indicator: for example , the postoperative mortality rate should be calculated in relation to the operated , not all patients.

4. When analyzing indicators, the Time factor should be taken into account:

it is impossible to compare indicators calculated for different periods of time: for example, the incidence rate for a year and for half a year , which can lead to erroneous judgments. 5. It is impossible to compare with each other the general intensive indicators calculated from sets that are heterogeneous in composition, since the heterogeneity of the composition of the medium can affect the value of the indicator.

Average values

Average values give a generalizing characteristic of the statistical population according to a certain changing quantitative attribute.

The average value characterizes the entire series of observations with one number, expressing the general measure of the trait under study. It levels out random deviations of individual observations and gives a typical characteristic of a quantitative trait.

One of the requirements when working with averages is the qualitative homogeneity of the population for which the average is calculated. Only then will it objectively reflect the characteristic features of the phenomenon under study. The second requirement is that the average value only expresses the typical sizes of a trait when it is based on a mass generalization of the studied trait, i.e. calculated on a sufficient number of observations.

Average values are obtained from distribution series (variation series).

Variation series- a number of homogeneous statistical values characterizing the same quantitative accounting attribute, differing from each other in their value and arranged in a certain order (decreasing or increasing).

The elements of the variation series are:

Option- v - numerical value of the studied changing quantitative trait.

Frequency- p (pars) or f (frequency) - the frequency of a variant in a variation series, showing how often one or another variant occurs in this series.

Total number of observations- n (numerus) - sum of all frequencies: n=ΣΡ. If the total number of observations is more than 30, the statistical sample is considered large; if n is less than or equal to 30, it is considered small.

Variational series are discontinuous (discrete), consisting of integers, and continuous, when the values of the variant are expressed as a fractional number. In discontinuous rows, adjacent options differ from each other by an integer, for example: the number of pulse beats, the number of breaths per minute, the number of days of treatment, etc. In continuous series, options can differ by any fractional value of one. Variation series are of three types. Simple- a series in which each option occurs once, i.e. frequencies are equal to one.

O bovine A series in which variants occur more than once.

grouped a ny- row. in which the options are combined into groups according to their size within a certain interval, indicating the frequency of occurrence of all options included in the group.

A grouped variational series is used with a large number of observations and a sick range of extreme values of the variant.

The processing of the variational series consists in obtaining the parameters of the variational series (mean value, standard deviation and average error of the mean value).

Types of averages.

In medical practice, the following averages are most often used: mode, median, arithmetic mean. Less commonly used are other averages: geometric mean (when processing the results of titration of antibodies, toxins, vaccines); root mean square (when determining the average diameter of a section of cells, the results of skin immunological tests); average cubic (to determine the average volume of tumors) and others.

Fashion(Mo) - the value of the trait, most often found in the aggregate. The mode is taken as the variant that corresponds to the largest number of frequencies in the variation series.

Median(Me) - the value of the trait, which occupies the median value in the variation series. It divides the variation series into two equal parts.

The magnitude of the mode and median is not affected by the numerical values of the extreme options available in the variation series. They cannot always accurately characterize the range of variations and are relatively rarely used in medical statistics. The arithmetic mean value characterizes the variation series more accurately.

With arithmetic mean(M, or) - is calculated on the basis of all numerical values of the studied trait.

In a simple variational series, where options occur only once, the simple arithmetic mean is calculated using the formula:

Where V - numerical values option,

n - number of observations,

Σ - sum sign

In the usual variational series, the arithmetic weighted average is calculated by the formula:

Where V is the numeric values of the option.

Ρ - frequency of occurrence of the variant.

n is the number of observations.

S - sum sign

An example of calculating the arithmetic weighted average is shown in Table 4.

Table 4

Determination of the average duration of treatment of patients in a specialized department of the hospital

In the example above, the mode is 20 days, since it is repeated more often than others - 29 times. Mo = 20. The serial number of the median is determined by the formula:

The place of the median falls on the 48th option, the numerical value of which is 20. The arithmetic mean, calculated by the formula, is also 20.

Mean values are important generalizing characteristics of the population. However, individual values of the attribute are hidden behind them. Average values do not show variability, fluctuation of the trait.

If the variation series is more compact, less scattered, and all individual values are located around the average, then the average value gives a more accurate description of this population. If the variation series is stretched, the individual values deviate significantly from the average, i.e. there is a large variability of a quantitative trait, then the average is less typical, worse reflects the entire series as a whole.

Averages of the same magnitude can be obtained from series with different degrees of scattering. So, for example, the average duration of treatment of patients in a specialized department of a hospital will also be 20 if all 95 patients were in hospital for 20 days. Both calculated averages are equal to each other, but obtained from series with varying degrees of variation.

Therefore, to characterize the variation series, in addition to the average value, another characteristic is needed , allowing to estimate the degree of its fluctuation.