Methodical instructions. The summary is a set of sequential operations to generalize specific single facts

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SUMMARY AND GROUPING

A summary is a set of sequential operations to generalize specific single facts that form a set in order to identify typical features and patterns inherent in the phenomenon under study as a whole.

The statistical summary should be maintained on the basis of a preliminary theoretical analysis phenomena and processes. The summary is simple and complex.

A simple summary is an operation to calculate the totals for a set of units of observation.

A complex summary is a set of operations that includes grouping observation units, counting totals for each group and for the entire object, and presenting the grouping and summary results in the form of statistical tables.

According to the form of processing, the summary can be decentralized and centralized. In the first case statistical information is processed in several stages: first, by regions, then it is aggregated, and as a result, indicators are obtained for the whole country. In the second - all primary material enters one organization, where it is processed from start to finish.

According to the technique of execution, the statistical summary is divided into mechanized and manual. With the advent of personal computers, manual summaries are rarely used.

To identify patterns, the grouping method is used.

Grouping is the division of the set of units of the studied population into groups according to certain characteristics that are essential for them. Grouping is one of the most methodologically difficult stages statistical study. The reasons for this are the complexity and diversity of socio-economic processes. Thus, the service sector consists of a number of sub-sectors and a large number enterprises. There are differences in capital equipment, staff composition, profitability, profitability, etc.

The following tasks are solved with the help of groups:

allocation of social economic types phenomena;

study of the structure of the phenomenon and structural changes occurring in it;

revealing the connection and dependence between phenomena.

TYPES OF STATISTICAL GROUPS

In accordance with the tasks to be solved, statistical groupings are divided into typological, structural and analytical.

Typological grouping is the division of a qualitatively heterogeneous population into classes or homogeneous groups. They are widely used in the study of socio-economic phenomena and allow us to trace the origin, development and death of various types phenomena.

grouping industrial enterprises by type of ownership

A grouping is called structural, in which a homogeneous population is divided into groups that characterize its structure according to some varying feature.

Grouping the population of Russia according to the size of the average per capita income

	Population groups by size of average per capita cash income, rub. per month	Population
		total, million people	in % of the total
	280 and more

These groupings show that more than 43% of the population has an average per capita cash income of 80 to 160 rubles. per month, income up to 40 rubles. received 1.6% of the population.

Changes in the structure of social phenomena reflect the most important patterns of their development.

Analytical grouping is called, revealing the relationship between the studied phenomena and their features.

Signs can be divided into factorial and effective. Factor signs are called signs, under the influence of which other signs, called effective ones, change. The relationship is manifested in the fact that with an increase in the value of the factor attribute, the average value of the indicator of the effective one systematically increases or decreases.

The features of the analytical grouping are as follows: firstly, the grouping is based on a factor sign; secondly, each selected group is characterized by the average values ​​of the resulting attribute.

Grouping of commercial banks in Russia by the amount of balance sheet assets

	Groups of banks by assets	Number of banks, units	Average per bank
			number of employees, people	balance sheet profit, billion rubles
	50,000 or more

These tables characterize the relationship between the amount of bank assets and the number of employees, as well as the amount of balance sheet profit. The method of analytical groupings is applicable only with the qualitative homogeneity of the studied population.

A grouping is called simple, in which groups are formed according to one attribute.

A grouping is called complex, in which the population is divided into groups according to two or more features taken in combination (combination). First, groups are formed according to one attribute (usually attributive), then they are divided into subgroups according to another attribute, which, in turn, are subdivided according to the third. (Usually no more than three).

Principles of construction of statistical groupings and classifications.

The grouping attribute or the basis of the grouping is the attribute by which the units of the population are divided into individual groups. Significant features should be used as the basis for grouping.

The number of groups depends on the objectives of the study, the type of trait underlying the grouping, the size of the population, and the degree of variation of the trait.

Classification should be distinguished from grouping. A classification is a stable fundamental grouping according to an attribute, which contains a detailed nomenclature of groups and subgroups. It is established by state and international statistics authorities. For example, the classification of occupations and occupations in labor statistics, the classification of goods in trade, etc.

When grouping by quantitative characteristics, you need to choose the size of the interval and set the number of groups accordingly. The number of groups depends on the range of variation i.e. the difference between the maximum and minimum values ​​of the feature. The greater the range of variation of the trait, the more groups are formed.

The number of groups n depends on the size of the studied population N. This dependence is expressed by the Sturgess formula.

Based on this formula, you can make a nomogram:

The grouping interval is defined as the difference between the maximum and minimum values ​​of a feature in each group.

If the variation of a trait manifests itself within relatively narrow boundaries, and the distribution is more or less uniform, then equal intervals are selected.

where i is the value of the interval, n is the number of groups, is the range of variation.

SECONDARY GROUPING is the formation of new groups based on a previously conducted grouping. Two ways:

Enlargement of initial intervals.

Shared rearrangement: the formation of new groups at smaller intervals.

The main tasks of the secondary grouping:

Formation of quantitative characteristics of qualitatively homogeneous groups.

For comparison: reduction to a single interval of two or more groupings.

The formation of enlarged groups in which the nature of the distribution comes through more clearly.

DISTRIBUTION RANKS

Statistical Series distribution - this is an ordered distribution of population units into groups according to a certain varying attribute. Depending on the trait underlying the formation of the grouping, there are attributive and variation distribution series.

Attributive called distribution series, built on qualitative grounds. Variational distribution series are called, built on a quantitative basis. Variation series consist of two elements: variants and frequencies. A variant is a separate value of a variable attribute, which it takes in a distribution series. Frequencies are the numbers of individual variants or each group of the variation series. Frequencies are called frequencies, expressed in fractions of a unit or percentage. The sum of the frequencies is the volume of the distribution series.

Depending on the nature of the variation of the trait, discrete and interval series are distinguished. A discrete distribution series is a series in which the numerical value of a feature is expressed as a certain integer. For example, the distribution of families by the number of rooms occupied:

With a continuous variation of a feature, interval variation series are constructed. The variant is given as an interval. When constructing interval series, it is necessary to determine the number of groups, types of intervals (equal, unequal, closed, open).

	Groups of families by size of living space per person, sq. m	Number of families with a given area size	Accumulated number of families

For the analysis of variational series, graphs are used: a polygon and a histogram.

The polygon is used when displaying discrete variational series. On the graph, a broken line is obtained, which is called a frequency polygon.

statistical grouping series distribution

When constructing a histogram of the distribution of a variational series with unequal intervals, along the ordinate axis, not the frequencies are plotted, but the distribution density of the feature in the corresponding intervals. This is done to eliminate the influence of the size of the interval on the distribution and to be able to compare frequencies. Distribution density is the frequency calculated per unit interval width.

The cumulate (sum curve) depicts a series of cumulative frequencies. The cumulative frequencies are placed along the y-axis, and the variants of the series are placed along the abscissa.

If, with a graphic representation of a variational series in the form of a cumulate, the axes are interchanged, then we get an ogive. With the help of cumulates, the process of concentration is depicted.

The distribution series is the simplest grouping, in which each distinguished group is characterized by one indicator - the number of object units that fall into each group.

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The concept and types of statistical grouping, produced in order to establish statistical relationships and patterns, to identify the structure of the population under study. Construction of an interval series for the distribution of enterprises on the basis of "sales space".

Based on the information collected in the course of statistical observation, as a rule, it is impossible to directly identify and characterize the patterns of socio-economic phenomena. This is due to the fact that observation provides information on each unit of the object under study. The data obtained are not general indicators. With their help, it is impossible to draw conclusions about the object as a whole without preliminary data processing.

So the goal of the next stage of statistical research is systematization of primary data and obtaining, on this basis, a summary of the characteristics of the entire object using generalizing statistical indicators.

Summary is a set of sequential operations to generalize specific single facts that form a set to identify typical features and patterns inherent in the phenomenon under study as a whole.

Thus, if during statistical observation data are collected about each unit of an object, then the result of the summary is detailed data that reflects the entire population as a whole.

The statistical summary should be based on a preliminary theoretical analysis of phenomena and processes. This is necessary in order not to lose information about the phenomenon under study during the report; in addition, all statistical results should reflect the characteristic features of the object.

The summary may be different, depending on a number of features that characterize it.

By the depth of data processing summaries are both simple and complex. simple summary is called the operation of calculating the totals for the totality of units of observation or the total volume of the studied indicator. For example, to get total number university students in Russia, it is enough to add up the data for all higher educational institutions in the country.

Complex summary is a set of operations that includes grouping observation units, counting the totals for each group and for the entire object, and presenting the grouping and summary results in the form of statistical tables.

The summary is preceded by the development of its program, which consists of the following stages:

choice of grouping features;

determination of the order of formation of groups;

development of a system of statistical indicators to characterize groups and the object as a whole;

development of a system of layouts of statistical tables in which the results of the summary should be presented.

By data processing form the summary is decentralized and centralized.

At decentralized summary(it is used, as a rule, in the processing of statistical reporting) the development of the material is carried out in successive stages.

At centralized summary all primary material goes to one organization, where it is processed from beginning to end. The centralized summary is usually used to process materials from one-time statistical surveys.

By performance technique the summary can be computer and manual.

computer summary- this is a way to perform a summary of statistical data, in which all operations are carried out using computers and software products that allow you to process any amount of information with varying degrees of detail. At manual summary all basic operations (calculation of group and general totals) are carried out manually.

To conduct a summary, a plan is drawn up that sets out organizational issues: by whom and when all operations will be carried out, the procedure for conducting it, and the composition of information to be published in the periodical press.

The most important stage in the study of socio-economic phenomena and processes is the systematization of primary data and, on this basis, obtaining a summary characteristic of the entire object using generalizing indicators, which is achieved by summarizing and grouping the primary statistical material.

Statistical summary - this is a complex of sequential operations to generalize specific single facts that form a set, to identify typical features and patterns inherent in the phenomenon under study as a whole. Conducting a statistical summary includes the following steps :

• choice of grouping feature;
• determination of the order of formation of groups;
• development of a system of statistical indicators to characterize groups and the object as a whole;
• development of layouts of statistical tables for presenting summary results.

Statistical grouping called the division of units of the studied population into homogeneous groups according to certain characteristics that are essential for them. Groupings are the most important statistical method generalization of statistical data, the basis for the correct calculation of statistical indicators.

Distinguish the following types groupings: typological, structural, analytical. All these groupings are united by the fact that the units of the object are divided into groups according to some attribute.

grouping sign is called the sign by which the units of the population are divided into separate groups. From right choice grouping feature depends on the conclusions of the statistical study. As a basis for grouping, it is necessary to use significant, theoretically substantiated features (quantitative or qualitative).

Quantitative signs of grouping have numeric expression(trading volume, age of a person, family income, etc.), and qualitative features of the grouping reflect the state of the population unit (sex, marital status, industry affiliation of the enterprise, its form of ownership, etc.).

After the basis of the grouping is determined, the question of the number of groups into which the study population should be divided should be decided. The number of groups depends on the objectives of the study and the type of indicator underlying the grouping, the size of the population, the degree of variation of the trait.

For example, the grouping of enterprises according to the forms of ownership takes into account municipal, federal and the property of the subjects of the federation. If the grouping is carried out on a quantitative basis, then it is necessary to invert Special attention on the number of units of the object under study and the degree of fluctuation of the grouping attribute.

When the number of groups is determined, then the grouping intervals should be determined. Interval - these are the values ​​of a variable characteristic that lie within certain limits. Each interval has its own value, upper and lower limits, or at least one of them.

The lower bound of the interval called smallest value feature in the interval, and upper bound - highest value feature in the interval. The interval value is the difference between the upper and lower limits.

Grouping intervals, depending on their size, are: equal and unequal. If the variation of the trait manifests itself in relatively narrow boundaries and the distribution is uniform, then a grouping is built with equal intervals. Value equal interval is determined by the following formula :

where Xmax, Xmin - maximum and minimum value trait in the aggregate; n is the number of groups.

The simplest grouping, in which each selected group is characterized by one indicator, is a distribution series.

Statistical distribution series - this is an ordered distribution of population units into groups according to a certain attribute. Depending on the trait underlying the formation of a distribution series, attributive and variation distribution series are distinguished.

attributive they call the distribution series built according to qualitative characteristics, that is, signs that do not have a numerical expression (distribution by type of labor, by sex, by profession, etc.). Attribute rows distributions characterize the composition of the population according to one or another essential feature. Taken over several periods, these data allow us to study the change in the structure.

Variation rows called distribution series built on a quantitative basis. Any variational series consists of two elements: variants and frequencies. Options the individual values ​​of the attribute that it takes in the variation series are called, that is, the specific value of the varying attribute.

Frequencies called the number of individual variant or each group of the variation series, that is, these are numbers that show how often certain variants occur in the distribution series. The sum of all frequencies determines the size of the entire population, its volume. Frequencies frequencies are called, expressed in fractions of a unit or as a percentage of the total. Accordingly, the sum of the frequencies is equal to 1 or 100%.

Depending on the nature of the variation of a feature, there are three forms of a variation series: a ranked series, a discrete series, and interval series.

Ranked variation series - this is the distribution of individual units of the population in ascending or descending order of the trait under study. Ranking makes it easy to divide quantitative data into groups, immediately detect the smallest and largest values ​​of a feature, and highlight the values ​​that are most often repeated.

Discrete variation series characterizes the distribution of population units according to a discrete attribute that takes only integer values. For example, the tariff category, the number of children in the family, the number of employees in the enterprise, etc.

If a sign has a continuous change, which within certain limits can take on any values ​​("from - to"), then for this sign you need to build interval variation series . For example, the amount of income, work experience, the cost of fixed assets of the enterprise, etc.

Examples of solving problems on the topic "Statistical summary and grouping"

Task 1 . There is information on the number of books received by students by subscription for the past academic year.

Build a ranged and discrete variational distribution series, denoting the elements of the series.

Decision

This set represents a set of options for the number of books students receive. Let us count the number of such variants and arrange them in the form of a variational ranked and variational discrete series distribution.

Task 2 . There is data on the value of fixed assets for 50 enterprises, thousand rubles.

Build a distribution series, highlighting 5 groups of enterprises (at equal intervals).

Decision

For the solution, we choose the largest and smallest values ​​of the cost of fixed assets of enterprises. These are 30.0 and 10.2 thousand rubles.

Find the size of the interval: h \u003d (30.0-10.2): 5 \u003d 3.96 thousand rubles.

Then the first group will include enterprises, the amount of fixed assets of which is from 10.2 thousand rubles. up to 10.2 + 3.96 = 14.16 thousand rubles. There will be 9 such enterprises. The second group will include enterprises, the amount of fixed assets of which will be from 14.16 thousand rubles. up to 14.16 + 3.96 = 18.12 thousand rubles. There will be 16 such enterprises. find the number enterprises included in the third, fourth and fifth groups.

The resulting distribution series is placed in the table.

Task 3 . For a number of light industry enterprises, the following data were obtained:

Make a grouping of enterprises according to the number of workers, forming 6 groups at equal intervals. Count for each group:

1. number of enterprises
2. number of workers
3. volume of manufactured products per year
4. average actual output per worker
5. amount of fixed assets
6. the average size fixed assets of one enterprise
7. average value of manufactured products by one enterprise

Record the results of the calculation in tables. Draw your own conclusions.

Decision

For the solution, we choose the largest and smallest values ​​of the average number of workers in the enterprise. These are 43 and 256.

Find the size of the interval: h = (256-43): 6 = 35.5

Then the first group will include enterprises with an average number of workers ranging from 43 to 43 + 35.5 = 78.5 people. There will be 5 such enterprises. The second group will include enterprises, the average number of workers in which will be from 78.5 to 78.5 + 35.5 = 114 people. There will be 12 such enterprises. Similarly, we find the number of enterprises included in the third, fourth, fifth and sixth groups.

We put the resulting distribution series in a table and calculate the necessary indicators for each group:

Conclusion : As can be seen from the table, the second group of enterprises is the most numerous. It includes 12 enterprises. The smallest are the fifth and sixth groups (two enterprises each). These are the largest enterprises (in terms of the number of workers).

Since the second group is the most numerous, the volume of output per year by the enterprises of this group and the volume of fixed assets are much higher than others. At the same time, the average actual output of one worker at the enterprises of this group is not the highest. The enterprises of the fourth group are in the lead here. This group also accounts for a fairly large amount of fixed assets.

In conclusion, we note that the average size of fixed assets and average value manufactured products of one enterprise are directly proportional to the size of the enterprise (in terms of the number of workers).

Ordering, systematization and generalization of statistical data are carried out at the second stage of statistical research in the process of summarizing and grouping 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 individual types, discover patterns and trends in their development.

Summary - is a set of sequential operations to generalize specific, single facts that form a set, to identify characteristic features and phenomena, as well as patterns inherent in the phenomenon under study.

According to the volume of work performed, the summaries are:

A simple summary is an operation to calculate the totals for a set of units of observation.

Complex summary - is a complex of operations, including grouping units of the population, calculating the totals for each group and for the entire object as a whole, and presenting the results of the grouping and summary in the form of statistical tables.

According to the form of processing the material, the summary is:

Decentralized - in which the development of the material is carried out in successive stages.

· Centralized - in which all primary material goes to one organization, where it is processed from start to finish.

According to the execution technique, the summary is:

· Mechanized - in which all operations are carried out with the help of electronic computers.

· Manual - in which all the main operations are carried out manually.

In accordance with the essence of the statistical summary as the second stage of the statistical study of the problem, it can be formulated as obtaining 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. On development stage programs

the subject and predicate of the summary are determined.

The subject is the object of study, divided into groups and subgroups.

Predicate - indicators that characterize the subject of the summary. The summary program is determined by the objectives of the statistical study.

However, one can distinguish general issues solved in the group summary program:

allocation of groups into which the totality should be divided, depending on the objectives of the study and the nature of the phenomena being studied;

determination of a list of grouping characteristics that allow attributing individual units of the studied population to one or another group within the selected system of groups;

establishing the boundaries of each group when grouping according to quantitative characteristics;

establishing a system of indicators for quantitative and qualitative characteristics dedicated groups.

The 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 performed in a decentralized and centralized manner. The plan of the statistical summary establishes the deadlines for the completion of each stage and the summary as a whole, as well as the ways in which the results of the summary are presented. These can be distribution series, statistical tables and statistical graphs.

Grouping is the division of the set of units of the studied population into groups according to certain characteristics that are essential for them.

Summary is a set of sequential operations to generalize specific single facts that form a set to identify typical features and patterns inherent in the phenomenon under study as a whole.

The result of the summary is detailed data that reflects the entire population as a whole.

According to the depth of material processing, the summary can be simple and complex.

simple summary is called the operation of calculating the totals for the totality of units of observation.

Complex summary- a set of operations, including grouping observation units, counting the results for each group and for the entire object, and presenting the grouping and summary results in the form of statistical tables.

The development of a summary program consists of the following stages: selection of grouping features; determination of the order of formation of groups; development of a system of statistical indicators to characterize groups and the object as a whole; development of a system of layouts of statistical tables in which the results of the summary should be presented.

According to the form of material processing, the summary is decentralized(the processing of the material is carried out in stages: for example, the reports of enterprises are summarized by the statistical authorities of the constituent entities of the Russian Federation, and the results for the region are already received by the State Statistics Committee of Russia) and centralized(all primary material goes to one organization, where it is processed from start to finish).

grouping called the division of the set of units of the population under study into groups according to certain characteristics that are essential for them.

Statistical groupings according to the tasks solved with their help are divided into: typological, structural and analytical.

Typological grouping- this is the division of the studied qualitatively heterogeneous population into classes, socio-economic types, homogeneous groups of units in accordance with the rules of scientific grouping. An example is the grouping of industrial enterprises by form of ownership.

When conducting a typological grouping, the main attention should be paid to identifying the types of socio-economic phenomena.

Structural called a grouping in which a homogeneous population is divided into groups that characterize its structure according to some varying feature.

Analytical grouping reveals the relationship between the studied phenomena and their features.

The group building process consists of the following steps.

1. Definition of a grouping attribute.

grouping sign is the sign by which the units of the population are divided into separate groups. It is often referred to as the base of the grouping.

Grouping can be based on both quantitative and qualitative characteristics. The former have a numerical expression (volume of trading, age of a person, etc.), and the latter reflect the state of a unit of the population (gender of a person, nationality, etc.)

The whole set of signs can be divided into two groups: factorial and effective. factorial called signs, under the influence of which other signs change and form a group productive signs.

2. Determining the number of groups.

The number of groups depends on the objectives of the study and the type of trait underlying the grouping, the size of the population. Degrees of variation of a trait.

When building a grouping qualitative feature there will be as many groups as there are gradations, species, states for this trait (gender - 2, regions of Russia - 89, etc.).

If the grouping is carried out on a quantitative basis, then

it is necessary to pay attention to the number of units of the object under study and the degree of fluctuation of the grouping attribute.

The greater the fluctuation of the grouping trait, the more groups should be formed.

If the distribution of the trait is conditionally uniform, then the Sturgess formula is used to determine the number of groups:

The disadvantage of the formula is that its application gives good results, if the population consists of a large number of units and the distribution of units on the basis of the grouping is close to normal.

3. Determination of the grouping interval.

Interval- the values ​​of the variable feature that lie within certain limits. Each interval has its own value, upper and lower limits, or at least one of them. The lower bound is the smallest feature value in the interval, and the upper bound is the largest feature value in it. Interval value is the difference between the upper and lower limits of the interval.

Grouping intervals depending on their size are equal and unequal. The latter are divided into progressively increasing, progressively decreasing, arbitrary and specialized.

If the variation of a trait manifests itself within relatively narrow boundaries and the distribution is more or less uniform, then a grouping is built with at equal intervals.

The value of an equal interval is determined by the following formula:

Before determining the range of variation, it is recommended to exclude anomalous observations (extreme points) from the population.

The resulting value is the interval step.

Open intervals- those with only one boundary.

Closed intervals- those that have both boundaries.

The width of the open interval is taken equal to the width of the adjacent closed interval.

Statistical distribution series- this is an ordered distribution of population units into groups according to a certain varying attribute.

Depending on the attribute underlying the grouping, there are attributive and variation distribution series.

attributive called rows built on qualitative grounds.

variational rows are called distribution rows built on a quantitative basis. Each variation series consists of two elements: variants and frequencies. Options the individual values ​​of the attribute that it takes in the variation series are considered, i.e. specific value of the variable attribute. Frequencies- these are the numbers of individual variants or each group of the variation series, showing how often one or another variant occurs in the series. Frequencies called frequencies, expressed as a percentage or fractions of a unit.

Depending on the nature of the variation of the trait, discrete and interval variation series are distinguished. In the case of discrete variation, the quantity quantitative trait takes only integer values. In the case of continuous variation, the value of the attribute in the units of the population can take any values ​​within certain limits.

The distribution series are analyzed using a graphical representation.

Polygon used in the display of discrete variational series. At the same time, the values ​​of the feature are plotted on the abscissa axis, and the frequencies are plotted on the ordinate axis.

bar graph used to display interval series. In this case, the intervals of the feature are plotted on the abscissa axis, and the frequencies are plotted on the ordinate axis. If the interval series is built with unequal intervals, then instead of frequencies, the distribution density of the feature in the corresponding intervals is plotted on the y-axis.

Distribution density is the frequency calculated per unit interval width.

A cumulative curve can also be used to display variation series. With help cumulates(sum curve) depicts a series of accumulated frequencies, which are determined by the successive summation of frequencies by groups and show how many units of the population have feature values ​​no greater than the considered value. The characteristic values ​​are plotted on the abscissa axis, and the accumulated frequencies are plotted on the ordinate axis. If, with a graphical representation of the cumulates, the axes are interchanged, then the result will be a graph called ogive.

Secondary grouping - an operation to form new groups based on a previously carried out grouping.

Two methods are used to form new groups:

1. The method of enlargement of intervals - the union of the original intervals - is used in the case of a transition from smaller intervals to larger ones, as well as in cases where the boundaries of new and old intervals coincide.

2. way fractional rearrangement– creation of new intervals based on assignment to each group certain share aggregate units.

Statistical called table, which contains numerical characteristic of the studied population according to one or more essential features, interconnected by the logic of economic analysis.

Logically, the table is statistical suggestion. Subject A statistical table is an object characterized by numbers. Usually the subject is located on the left side of the table, in the name

lines. Predicate the statistical table forms a system of indicators that characterize the subject (object of study). The predicate forms the top headings and makes up the contents of the graph.

According to the nature of the subject, they distinguish simple and complex tables. Simple tables are monographs and lists. Complex tables, in turn, are divided into group and combination.

If only one group or one object is represented in the subject, then the table is called simple monographic. If the subject contains an ungrouped list of units, then the table is called simple listing.

If the subject presents a grouping of population units according to one attribute, then the table is called complex group. If the subject presents a grouping of units according to several criteria, then the table is called complex combinational.

According to the development of the predicate, tables with simple and complex development of the predicate. At simple In the development of the predicate, the indicator that defines it is not divided into subgroups, and the final values ​​are obtained by simply summing up the values ​​for each feature separately, independently of each other.

Complex the development of the predicate involves the division of the attribute into subgroups that form it.

There are many types graphic images. Classification of chart types is shown in fig. 3.1.