Statistics are multidiscipline, as it uses methods and principles borrowed from other disciplines. So, as a theoretical base for the formation of statistical science, knowledge in the field of sociology and economic theory is served. As part of these disciplines, the laws of public phenomena take place. Statistics helps to assess the scale of one or another phenomenon, as well as develop a system of methods for analyzing and learning. Statistics are undoubtedly associated with mathematics, as it requires a number of mathematical operations, methods and laws to identify patterns, evaluating and analyzing the object of study, and the systematization of the results is reflected in the form of graphs and tables.

Types of statistical studies

Observation as the initial stage of research is associated with the collection of source data on the issue studied. It is characteristic of many sciences. However, every science has its own specifics, differing in its observations. Therefore, not any observation is statistical.

Statistical research is a scientifically organized collection, summary and analysis of data (facts) on socio-economic, demographic and other phenomena and public life processes in the state with the registration of their most essential signs in the accounting documentation.

Distinctive features (specific) of statistical research are: focus, organization, massiness, systemicity (complexity), comparability, documentation, controllability, practicality.

In general, the statistical study should:

Have a socio-beneficial goal and universal (state) significance;

Refer to the subject of statistics in specific conditions of its place and time;

Express a statistical type of accounting (and not accounting and not operational);

Conducted according to a previously developed program with its scientifically based methodological and other security;

Carry out the collection of mass data (facts), which reflects the entire set of causal and other factors, versatile characterizing the phenomenon;

Register in the form of account documents of the established sample;

Guarantee no observation errors or reduce them to a possible minimum;

Provide certain quality criteria and methods for monitoring the collected data, ensuring their accuracy, completeness and meaningfulness;

Focus on cost-effective data collection and data processing technology;

Being a reliable information base for all subsequent stages of statistical research and all users of statistical information.

Studies that do not satisfy these requirements are not statistical. Are not statistical studies, such as observations and research: mother for a playing child (personal question); viewers for theatrical formulation (no accounting documentation on spectacular); scientist for physicochemical experiments with their measurements, calculations and documentary registration (not massive-public data); doctor for patients with medical records (operational accounting); accountant for cash flow on the bank account of the enterprise (accounting); journalists for public and personal vital activity of public individuals or other celebrities (not subject to statistics).

The statistical aggregate is a set of units with massiness, typical, high-quality homogeneity and the presence of variation.

The statistical aggregate consists of material objects (employees, enterprises, countries, regions), is the object of statistical research.

Statistical observation is the first stage of a statistical study, which is a scientifically organized collection of data on studied phenomena and public life processes.

Statistical tables.

Plan.

1. Concept of statistical table. Elements of a statistical table.

2. Types of tables by the nature of the subject.

3. Types of tables for the development of the fad.

4. Basic rules for building tables.

5. Reading and analyzing the table.

1. Concept of statistical table. Elements of a statistical table.

The results of the summary and grouping of materials of statistical observation are usually set out in the form of tables that make information foreseeable.

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

In this way, statistical is called Tablewhich contains a consolidated numerical characteristic of the total combination of one or several essential features, interrelated logic of economic analysis. Statistical table - The form of rational and visual presentation of the digital characteristics of the studied phenomena.

The statistical generalization of information and presenting it in the form of consolidated statistical tables makes it possible to characterize the dimensions, structure and dynamics of studied phenomena. Often, a general header is given to the statistical table, which indicates the content of the table, the location and time to which the data refer to the table, as well as the measurement units, if they are the same for all the information provided.

Elements of a statistical table

The main elements of the statistical table presented in Figure 1 make up its basis.

Table name * (shared title)

	Name graph (upper headers)
BUT
Name of string (side headers)
Final string						Final graph

* Notes to the table

Fig. 1. Osters (base) of the statistical table

The statistical table contains three types of titles:

The overall header reflects the content of the entire table (to which place and it belongs to it), it is located above its layout in the center and is an external heading. The upper headers characterize the content of the graph (headlines of the facility), and the side (headlines of the subject) - the term. They are internal headlines. Table headers must be brief and disclose the content of indicators.

Digital material can be represented by absolute (population of the Russian Federation), relative (price indices for food products) and average (average monthly income of the serving commercial bank) values.

If necessary, the table may be accompanied by a note used in order to explain the headers, the methods of calculating some indicators, sources of information, etc.

By logical content, the table is a "statistical proposal", the main elements of which are subject to both the faith.

Subject to The statistical table is called an object characterized by numbers. These may be one or more aggregate, individual units of aggregate (firms, associations) in the order of their list or grouped by any signs (individual territorial units or time periods in chronological tables, etc.). Typically, the subject table is given in the left side, in the name of the lines.

Predicate The statistical table forms a system of indicators that are characterized by an object of study, i.e. subject to table. The surehead forms the upper headers and constitutes the content of the graph with a logically sequential position of the indicators from left to right.

The location of the subject and the facility can vary in places, which depends on the achievement of each researcher separately the most complete and better way to read and analyze the initial information on the totality studied.

2. Types of tables by the nature of the subject.

The view of the statistical table depends on the construction of the subject. From this point of view tables are there:

Simple;

Sophisticated:

Group;

Combinational.

Simple called tablein which the object of the study is not divided into groups. In this case, two options are possible:

1) the table contains data on the totality as a whole;

2) The table contains data on each unit of aggregate.

The latter is justified if the number of units is small. For example, the table shows the data for each of the 13 cities - millionaires of the Russian Federation. A data table for each unit can be used as a working material for any subsequent calculations.

In a simple table, a simple list of any objects or territorial units is given, i.e. A group of units of aggregate is subject to. Simple tables are monographic and lugs. Monographic tables are not characterized by the entire set of units of the object being studied, but only one large group of it, isolated on a certain, in advance formed by the sign.
Simple luggage tables are called tables that are subject to which contains a list of units of the object being studied.

An example of a simple table serves Table. one.

Table 1

The volume of basic communication services of the Russian Federation

Source: social status and living standard of Russia. Statistical compilation. M.: Goskomstat of Russia, 2000. P. 411.

Subject to this table is made in the title table; The table itself is a surehead, and the values \u200b\u200bof the indicators are given in dynamics.

Group table - This is a table in which subject, i.e., the object of the study is divided into groups on any one feature (Table 2).

table 2

Distribution by the level of education (according to selective surveys of the Russian Federation on employment issues)

The level of education
Including:
higher professional
incomplete higher professional
curly professional
average (full) general
main general
do not have the main common

Source: social status and living standard of Russia. Statistical compilation. M.: Goskomstat of Russia, 2000. P. 80.

Combination table Includes subject to which the research object is divided into groups on two or more signs. For example, Table. 3 will become a combination, if the unemployed is subdivided into groups not only in terms of education, but also by the floor. At the same time, the following options for building a table are possible.

1st Option: The subject is located on the left side of the table-group allocated on one basis, are divided into subgroups on another basis. Schematically, it looks like this:

2nd option: Subject to the left and upper parts of the table. The table has the form:

3. Types of tables for the development of the fad.

In the limit of the statistical table, as mentioned, indicators are given, which are the characteristic of the object being studied. This characteristic can be given by a small number of indicators or a whole system of indicators.

According to the structural structure of the facility, the statistical tables with a simple and difficult development are distinguished.

For simple development of the fad The indicator that determines it is not subdivided into subgroups, and the total values \u200b\u200bare obtained by simply summing the values \u200b\u200bfor each character separately independently of each other. An example of a simple development of the facility can be the following fragment of the statistical table.

After filling in this fragment of the table, a detailed characteristic of privatized enterprises in the structure of their subjects - owners is obtained. For each enterprise, you can get information on the number and price conditions for the sale of shares.

Complex development of the tagimplies the division of a feature forming it to the subgroups.

Distribution of shares among employees of privatized enterprises of industry

With the complex development of the facility, a more complete and detailed characteristic of the object is obtained.

The combined development of indicators under the terms of the sale of shares and their species allows to deepen the economically - a statistical analysis of the stock market and its structure for privatized enterprises.

Here both signs of the faithful (price and species) are closely connected with each other. It is possible to analyze not only the number of acquired shares by type and conditions for the acquisition by their employees of privatized enterprises, but also identify the number of preferred and ordinary shares acquired on different price conditions. So, in case of complex development of the lean, each group of enterprises or each enterprise can be described separately by various combination of features that form a legend.

However, the complex development of the faugible can lead to an immeasurable increase in the dimension of statistical tables, which, in turn, reduces their visibility, reading and analysis.

Therefore, the researcher in the construction of statistical tables should be guided by the optimal ratio of the indicators of the faded and take into account both positive and the negative points of the complex development of the indicators of the facility.

4. Basic rules for building tables.

Statistical tables as a means of visual and compact presentation of digital information must be statistically correctly decorated.

The main techniques that define the technique of forming statistical tables are as follows.

1. The table must be compact and contain only those source data that directly reflect the socially-studied economic phenomenon in statics and dynamics and is necessary for the knowledge of its essence.

It should be avoided by an unnecessary, secondary, non-delayed information to this object of information. Digital material must be described in such a way that when analyzing the table, the entity of the phenomenon has revealed by reading the strings from left to right and top down.

2. The title of the table and the names of the graph and strings must be clear, briefs, laconic, represent the complete integer, which is organically fit into the content of the text.

It is necessary to avoid a large number of points and commas in the table names and the graph that impede the reading of the table.

If the table name consists of two or more suggestions, the point is put to separate the proposals from each other, but not after the last.

In the headlines, the count is allowed only with the necessary abbreviations.

The title tables should find reflection object, sign, time and place of event. For example: "US dollar rate at the MICEX trading in 1997" But at the same time it should be remembered that the more rake and laconic the text of the table heading, the more clear and more intelligible for reading and analyzing, naturally, if it is carried out not to the detriment of its accuracy and informality. Table headers, graph and lines are written completely, without abbreviations.

3. The information located in the columns (graphs) of the table is completed with the final string. There are various ways to connect the term graph with their outcome:

the string "Total" or "total" completes the statistical table;

the final line is located in the first line of the table and is connected to the combination of its terms with the words "including".

In group and combinational tables, it is always necessary to give final graphs and lines.

5. If the names of the individual graph are repeated among themselves, contain repeating terms or carry a single semantic load, then they need to assign a common combining header.

This reception is used for both to be, and for the faded tables.

6. Graphs and lines are useful to numbered. The graphs on the left filled with the name of the lines are made to be denoted by capital letters of the alphabet (A), (B), etc., and all subsequent graphs - numbers in ascending order.

7. Interrelated and interdependent data characterizing one of the sides of the analyzed phenomenon (for example, the number of enterprises and the proportion of factories (in% to the result), the absolute increase and growth rate, etc.), it is advisable to have in neighboring graphs.

8. Counts and lines must contain units of measurement corresponding to the indicators supplied to and beyond. At the same time, generally accepted reductions of the units of measurement are used (people, rub., KW / h, etc.).

9. It is best to have a digital information compared in the tables during the analysis in the same graph, one for another, which greatly facilitates the process of comparison.

Therefore, in group tables, for example, the group on the studied attribute to more competently position in descending order or increase its values \u200b\u200bwhile maintaining a logical connection between the tables subject to and led.

10. For the convenience of the number of the number in the tables, it is necessary to represent in the middle of the graph, one under another: units under units, a comma dive, which is clearly observing their discharge.

11. If the number is possible, it is advisable to round. Rounding the numbers within the same graph or string should be carried out with the same degree of accuracy (to a whole sign or up to the tenth, etc.).

If all the numbers of the same graph or string are given with one decimal, and one of the numbers has two or more decimal sign, the numbers with one sign after the comma should be supplemented with zero, thereby emphasizing their equal accuracy.

12. The lack of data on the analyzed socio-economic phenomenon may be due to various reasons, which is different in the table:

a) if this position (at the intersection of the relevant graphs and strings) is generally not filled, then the sign "X" is put;

b) When for some reason there are no information, then the "..." or "no shortcut", or "N. sv. ";

To display very small numbers, the notation (0.0) or (0.00) is used, which implies the ability to have a number.

13. If you need additional information - clarification - notes can be given to the table.

Compliance with the rules for constructing and designing statistical tables makes them the main means of representation, processing and generalization of statistical information on the status and development of the analyzed social and economic phenomena.

5. Reading and analyzing the table.

Analysis of statistical tables is preceded by the stage of familiarization - their readings.

Reading and analyzing tables should be carried out not chaotic, but in a certain sequence.

Reading assumes that the researcher, reading the words and numbers of the table, learned its content, formulated the first judgments about the object, understood the purpose of the table, understood its content as a whole, gave an assessment of the phenomenon or the process described in the table.

Table Analysis As a method of scientific research by splitting the subject of study on parts is divided into structural and meaningful.

Structural analysis involves an analysis of the structure of the table, the characteristic of the tables presented in the table:

combustion and units of observation forming it;

the signs and their combinations forming the subject and the target table;

signs: quantitative or attribute;

the ratio of signs of subjects subject to indicators;

type view: Simple or complicated, and the last - group or combination;

observed tasks - analysis of the structure, types of phenomena or their relationships.

Subtle analysis It assumes the study of the internal content of the table: the analysis of individual groups of subject to the appropriate features of the said; identifying the ratio and proportions between groups of phenomena on one and different features; Comparative analysis and wording of conclusions for individual groups and throughout the whole; Establishment of patterns and identification of reserves for the development of the object being studied.

Before you begin to analyze numerical information, it is necessary to test its accuracy and scientific validity. The researcher must ensure the reliability and reliability of the data source of data and critically evaluate their digital values. You should make logical and counting data verification. Logical check It consists in the possibility of determining specific signs of those or other numerical values \u200b\u200b(for example, it is absurd if the number of employees on the firm amounted to 106.7 people). Counting check It assumes the selective calculation of the individual values \u200b\u200bof the characteristic of the group, or the final values \u200b\u200bof rows or graph, etc.

The analysis of these tables is performed for each basis separately, then in the logical - economic combination of the entire set of signs in general.

An analysis of individual features and groups should be started with the study of absolute, then associated with relative values. When analyzing the data, you should consider the dynamics of each trait for the entire period, moving from one to another.

Table analysis can be supplemented with calculated relative and average values \u200b\u200bif the objective tasks are required.

To obtain a more complete and visual representation of the studied phenomena and processes according to statistical tables, graphs, diagrams, etc. are being built.

Analysis of group and combinational tables allows you to characterize the types of social and economic phenomena, the structure of the aggregate, relationship and proportion between individual groups and units of observation; To identify the nature and direction of relationships and interdependencies between different, certain logic of economic analysis, combinations of signs and dependence of signs - the investigation of the signs - the reasons.

Compliance with the rules and sequences of working with statistical tables helps the researcher implement a scientifically based economically - statistical analysis of objects and processes.

Graphic image of statistical data.

Plan

1. Concept of statistical graphics. Elements of statistical graph.

2. Classification of graphs.

3. Comparison diagrams.

4. Structural diagrams.

5. Dynamics charts.

1. Concept of statistical graphics. Elements of statistical graph.

For the first time on the technique of drawing up statistical graphs, the work of the English economist W. Playfeira "Commercial and Political Atlas", published in 1786 and putting the beginning of the development of methods of graphic image of statistical data.

C.tatistic chart- This is a drawing on which statistical aggregates characterized by certain indicators are described using conventional geometric images or signs. The presentation of these tables in the form of a graph produces a stronger impression than figures, it makes it possible to better comprehend the results of statistical observation, correctly interpret them, greatly facilitates the understanding of the statistical material, makes it visual and affordable.

When building a graphic image, a number of requirements should be followed. First of all, the schedule should be quite visual, since the entire meaning of the graphic image as a method of analysis in that consists in order to visually depict statistical indicators. In addition, the schedule must be expressive, intelligible and understandable. To fulfill the above requirements, each schedule must include a number of major elements: graphic image; Graphics field; spatial landmarks; large-scale landmarks; Operating schedule.

Graphic Image (Base Graphics)- These are geometric signs, i.e. The totality of points, lines, figures with which the statistical indicators are depicted. Graphic are those images in which the properties of geometric signs are a figure, the size of the lines, the location of the parts - are essential to express the content of the depicted statistical values, and each change in the expressed content corresponds to the change in the graphic image.

Graphics field- This is part of the plane where graphic images are located. The graph of the graph has certain dimensions that depend on its purpose.

Spatial landmarksgraphics are specified as a system of coordinate grids. The coordinate system is necessary to place geometric signs in the graph field. The most common system of rectangular coordinates is the most common.

To build statistical graphs, it is usually used only the first occasionally the first and fourth squares. Polar coordinates also apply in the practice of graphic image. They are needed for a visual image of cyclic movement in time. In the polar coordinate system (Fig. 2), one of the rays, usually right horizontal, is used for the coordinate axis, relative to which the beam angle is determined. The second coordinate is its distance from the center of the grid, called the radius. In radial graphs, the rays indicate the moments of time, and the circumference - the values \u200b\u200bof the studied phenomenon. On statistical machines, spatial landmarks are defined by the contour mesh (river contours, the coastline M

Fig. 2.. Polar coordinate system

Ore and oceans, borders of states) and determine the territories to which statistical values \u200b\u200bare.

Large-scale landmarksstatistical graphics are determined by the scale and system of large-scale scales. The scale of the statistical chart is a measure of a numerical value in graphical.

Large scalethe line is called, some points of which can be read as certain numbers. The scale is of great importance in the column and includes three elements: a line (or carrier of the scale), a certain number of marked dots, which are located on a scale carrier in a specific order, digital designation of numbers corresponding to individual marked points.

The carrier of the scale can be both direct and curved lines. Therefore, the scales are distinguished straightforward(for example, a millimeter line) and curvilinear - arc and circular (clock cloust).

Scale of the uniform scale is called length Cut(Graphic interval) adopted per unit and measured in any measures.

Graphic and numeric intervals are equal and unequal.

For the most part, uniform scales are used, when equal number values \u200b\u200bcorrespond to equal graphic segments.

An example of an uneven scale can be the logarithmic scale, which is used with a large scale of the levels of the indicator and in the spotlight are, as a rule, are not absolute, but relative changes.

Last element graphics - explication. Each schedule must have a verbal description of its content. It includes its content; Signatures along scale scales and explanations to individual parts of the graph.

2. Classification of graphs.

Types of graphs. Depending on the field, statistical graphics divide on statistical diagramsand statistical maps.

Charts in turn are the following:

Comparisons and display;

Structural;

Speakers;

Special.

Statistical cards reflect the statistical-geographical incision of the data, show the placement of the phenomenon, the process on the territory. They are divided by cartogram and Cardagramma.

Comparison and Display Charts. Comparison and mapping charts graphically show the ratio of various statistical aggregates or units of a statistical aggregate according to any varying attribute. These charts in most cases are shown on the chart field of the chart of the incident, histogram and polygon.

Structural charts. Structural diagrams make it possible to compare statistical aggregates in composition. This is primarily the specific science diagrams characterizing the ratio of individual parts of the aggregate to its total volume. By sight, they are divided into columns and sectors.

Dynamics charts. Dynamics diagrams are used to display changes in time. Such a change can be represented by a bar or bandage diagram in which each column or band reflects the amount of the phenomenon to a specific date or for a certain period of time. Sometimes it is advisable to use circular and square charts in which the phenomenon is displayed the circles or squares, the values \u200b\u200bof the radii and sides of which are proportional to square roots from absolute signs.

Communication Charts (Graphics). Communication charts are built using curves showing the link between features, one of which is a resultful (dependent), the second - factor (independent) (Fig. 3).

Fig. 3. The dependence of the feed consumption per cow per year from productivity

Ohiva Gilton and Cumulat. Ogon is called a graphic image of a row of distribution in ascending order or descending of the varying feature. Here, as a rule, according to the axis, the ordinates lay the signs of the feature, and along the abscissa axis - the units of the aggregate (in rank).

For a row, it can be clearly judged on the minimum and maximum values \u200b\u200bof the feature, according to its steepness - on the uniformity of the distribution and homogeneity of the units of the set (Table 3, Fig. 4).

Table 3.

Distribution of workers brigades No. 21 and No. 32 AVANGARD JSC in terms of qualification (discharges) and ranks on July 1, 1998 *

Brigade number 21.			Brigade number 32.
tabel No.			tabel No.

* Example conditional.

Fig. four. Distribution of Works Brigades No. 21 (a) and No. 32 (6) Avangard JSC in terms of qualification (discharges) and ranks as of July 01, 1998:

a) equal intervals

Fig. four. Continued

b) unequal intervals

Cumulat - This is a graph depicting a number of accumulated frequencies. Here, according to the abscissa axis, the values \u200b\u200bof the feature are deposited, and along the ordinate axis - the increasing results of the frequencies (Fig. 5).

Fig. five. Cumulating distribution of the population of the Tver region on average foreign monetary income in 1996

Cartograms. Cartograms, or statistical maps, illustrate the content of statistical tables to be subject to administrative or geographical division of the aggregate. Here, as a field of graphics, geographical maps are located on which statistical tables (centogram) are placed, various color or background, conditional symbols are used (Fig. 6).

Fig. 6. The scheme of the natural economic zoning of the Tver region.

3. Comparison diagrams.

Comparison and mapping charts graphically show the ratio of various statistical aggregates or units of a statistical aggregate according to any varying attribute.

These charts in most cases are shown on the chart field of the chart of the incident, histogram and polygon.

Casus diagram. The chart of the incident is the display of the varying feature in the sequence in which it is recorded. Here, along the abscissa axis, there are units of aggregate, and along the ordinate axis - the sign values. For example, in Fig. 7 With the help of the chart of the incident, the number of cattle in the farms of all categories in the Central Zone of the Tver Region (Areas: 1- Kalininsky, 2-Kalyazinsky, 3-Kimirsky, 4-Konakovsky, 5-Kuvyovsky, 6-Likhoslavl, 7-Maksatikhinsky , 8-Rameshkovsky, 9-Spearovsky, 10-Town).

Fig. 7.The dynamics of cattle livestock in the farms of all categories in the regions of the central zone of the Tver region.

Bar graph. The histogram is called a graph on which a number of distribution is depicted in the form of adjacent columns. It is usually used for the image of the interval distribution series. Here, on the abscissa axis, the signs are deposited, and according to the ordinate axis - frequency.

When building histograms, the scales is not allowed. In the event that the compared sets are different in size, it is not frequencies on the ordinate axis, but relative frequencies (specific gravity or shares of the entire totality). (Fig. 8)

Fig. eightThe distribution of the population in size of the average
monetary income in 2010 for the first quarter.

Polygon. The polygon is called a graph on which a number of distributions are depicted as a linear chart. It is usually used for the image of discrete distribution series. Here, along the abscissa axis, the values \u200b\u200bof the varying feature are deposited, and along the ordinate axis - frequency (frequency).

In fig. 9 shows a distribution polygon costly environmental protection across the Russian Federation in 2009 according to Table. four.

Fig. nine Distribution costly environmental protection across the Russian Federation in 2009.

The cost of environmental protection in the Russian Federation in 2009
(in actually acting prices; millions of rubles)

	Symbol	Passed million rubles	In% to the outcome
protection of atmospheric air
sewage treatment
deployment of waste
protection and rehabilitation of soil, underground and surface water
preservation of biodiversity and habitats

4. Structural diagrams.

Structural diagrams make it possible to compare statistical aggregates in composition. This is primarily the specific science diagrams characterizing the ratio of individual parts of the aggregate to its total volume. By type, they are divided into columns (Fig. 10) and sectoral (circular) (Fig. 11).

1990 1996

Fig. 10. Structure of production main funds of agricultural enterprises of the Tver region

Peasantic

(farmer) farms

Fig. eleven. Gross Products of Agriculture of the Tver Region in 1996

Using sector structural charts, it is necessary to remember that 1% corresponds to 3.6 °. In structural diagrams, specific weights or the structure itself are isolated using hatching or coloring.

5. Dynamics charts.

Dynamics diagrams are used to display changes in time. Such a change can be represented by a bar or bandage diagram in which each column or strip reflect the amount of the phenomenon to a specific date or for a certain period of time (Fig. 12, 13).

1990 1991 1992 1993 1994 1995 1996 1997

Fig. 12. Real salary of workers and employees of the Russian Federation (1990 - 100%)

0 200 400 600 800 1000

Fig. 13. Grain production in the Tver region (in the initially credited weight)

Sometimes it is advisable to use circular and square diagrams in which the phenomenon is displayed or squares, the values \u200b\u200bof the radii and sides of which are proportional to square roots from absolute signs (Fig. 14).

Fig. fourteen. Sowing areas of peasant (farmer) farms of the Tver region, thousand ha

In most cases, the process dynamics is displayed with a linear diagram (Fig. 15).

Fig. fifteen. The share of agriculture in the WFP of the Russian Federation, in 1989-1997.

One of the types of diagrams are radial, which are used to display phenomena, periodically repeated over time (for example, seasonal oscillations, Fig. 16).

Fig. sixteen. Egg production chickens of the N-th poultry farm for months on average for 1995 - 1997.

To construct radial (petal) diagrams, the circle is divided into parts by the number of periods. The radius of the circle for each period determines the value (absolute or relative) phenomena.

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Statistics- Science, which studies the quantitative side of mass socio-economic phenomena and processes, in an inseparable unity with their qualitative side in specific conditions of place and time.

In the natural sciences, the concept of "statistics" means an analysis of mass phenomena based on the use of probability theory methods.

Statistics are developing a special methodology for research and processing materials: mass statistical observations, grouping method, average values, indexes, balanced method, method of graphic images.

Methodological features is the study: the mass of phenomena, qualitatively homogeneous signs of one or another phenomenon in the dynamics.

Statistics include a number sections Of which: General Statistics Theory, Economic Statistics, Industry Statistics - Industrial, Agriculture, Transport, Medical.

11. Groups of indicators to assess the health of the population.

The health of the population is characterized by three groups of the main indicators:

A) Medico-demographic - reflect the condition and dynamics of demographic processes:

Population statistics (density, accommodation, social composition, composition on sex and age, literacy, education, nationality, language, culture.)

Dynamics of the population (mechanical emigration and immigration, natural fertility, mortality, natural increase.)

Family state (wreck ratio, divorce, average duration of marriage.)

Reproduction processes (total fertility, gross coefficient and net coefficient.)

Average life expectancy

Mortality (mortality structure, mortality rates depending on the cause, nature of morbidity and age.)

B) Indicators of morbidity and injuries (primary morbidity, prevalence, accumulated morbidity, pathological affection, health index, mortality, injury, disability.)

C) Indicators of physical development:

Anthropometric (growth, body weight, chest circumference, head, shoulder, forearm, leg, hips)

Physiometric (life capacity of the lungs, muscular power of hands, rainfall)

Somatoscopic (physique, muscle development, degree of fatness, thoracic shape, shape of the legs, stop, severity of secondary sexual signs.)

Medical statistics, its sections, tasks. The role of the statistical method in exploring the health of the population and the activities of the health system.

Medical (sanitary) statistics -he examines the quantitative side of the phenomena and processes associated with medicine, hygiene and health.

Allocate 3 sections of medical statistics:

1. Public health statistics - studies the state of health of the population as a whole or its individual groups (by collecting and statistical analysis of data on the number and composition of the population, its reproduction, on natural movement, physical development, prevalence of various diseases, lifespan, etc.). Assessment of health indicators is carried out in comparison with generally accepted estimated levels and levels obtained by various regions and in dynamics.

2. Health statistics - solves the issues of collecting, processing and analyzing information about the network of health institutions (their placement, equipment, activity) and personnel (about the number of doctors, middle and junior medical staff, about the distribution of them by specialties, experience work, about their retraining, etc. .). When analyzing the activities of medical and preventive institutions, a comparison of the data obtained with regulatory levels is made, as well as the levels obtained by other regions and in the dynamics.

3. Clinical Statistics - this is the use of statistical methods in the processing of the results of clinical, experimental and laboratory studies; It makes it possible from a quantitative point of view to evaluate the accuracy of the results of the study and solve a number of other tasks (determining the volume of the required number of observations in the sample study, to form an experimental and control group, to study the presence of correlation and regression bonds, eliminate the qualitative heterogeneity of groups, etc.).

The tasks of medical statistics are:

1) Studying the health of the population, analysis of the quantitative characteristics of public health.

2) identifying links between health indicators and various factors of natural and social medium, assessment of the influence of these factors at the level of health of the population.

3) learning material - technical health base.

4) Analysis of the activities of therapeutic and preventive institutions.

5) Evaluation of the effectiveness (medical, social, economic) medical, preventive, anti-epidemic activities and health care as a whole.

6) the use of statistical methods during clinical and experimental biological research.

Medical statistics are a method for social diagnostics, since it allows us to evaluate the health of the country's population, region, and on this basis to develop measures aimed at improving public health. The most important principle of statistics is to use it to explore not separate, single, and mass phenomena, in order to identify their general patterns. These patterns manifest themselves, as a rule, in the mass of observations, that is, when studying a statistical aggregate.

In medicine, statistics are the leading method, because:

1) allows you to quantify the health indicators and the performance of medical institutions

2) determines the effect of the influence of various factors on the health of the population

3) Determines the effectiveness of treatment and health events

4) Allows you to estimate the dynamics of health indicators and allows you to predict them

5) allows you to get the necessary data for the development of norms and health standards.

Statistical aggregate. Definition, types, properties. Features of the study of the statistical aggregate.

The object of any statistical research is a statistical aggregate.

Statistical aggregate - A group consisting of a set of relatively homogeneous elements, taken together in the known boundaries of space and time and possessing signs of similarities and differences.

Properties of statistical aggregate: 1) homogeneity of observation units 2) certain boundaries of the space and time of the studied phenomenon

The object of statistical research in medicine and health care can be various contingents of the population (the population in the whole or its individual groups, patients, dead, born), therapeutic and preventive institutions, etc.

Distinguish two types of statistical aggregate :

a) general aggregate

b) selective aggregate

1. The selective set is formed in such a way as to ensure equal opportunity for all elements of the original set of observation.

2. The selective set must be representative (representative), accurately and fully reflect the phenomenon, i.e. Giving the same idea of \u200b\u200bthe phenomenon as if the entire general aggregate was studied.

Selective aggregate

1) must be representative, accurately and fully reflect the phenomenon, i.e. Giving the same idea of \u200b\u200bthe phenomenon as if the entire general aggregate was studied, for this it should:

but. be sufficient

b. have the main features of the general population (all elements in the selected part must be presented in the same relation as in general)

2) when it is formed, must be observed

1) random selection - Selection of observation units by draw using a table of random numbers, etc. At the same time, for each unit, an equal opportunity to get into the sample is ensured.

2) mechanical selection - the units of the general population, consistently located according to any sign (according to the alphabet, by dates of appeal to the doctor, etc.) are divided into equal parts; From each part in a predetermined procedure, each 5, 10 or N-th of the observation unit is taken in such a way as to ensure the necessary sampling.

3) typical (typological) selection - assumes a mandatory preliminary dismemberment of the general population into separate qualitatively homogeneous groups (types), followed by a sample of observation units from each group by subbands of random or mechanical selection.

4) Serial (nest, nest) selection - suggests a sample from the general population of non-individual units, but a total series (organized a combination of units of observations, for example, organizations, districts, etc.)

5) K. ombinizedmethods - a combination of various ways to form a sample.

Selective set, requirements for it. Principles and ways of forming a selective aggregate.

Distinguish two types of statistical aggregate :

a) general aggregate - A combination consisting of all observation units that may be related to it in accordance with the aim of the study. When studying public health, the general population is often considered within the specific territorial borders or may be limited to other signs (floors, age, etc.) depending on the purpose of the study.

b) selective aggregate - Part of the General, selected by a special (selective) method and intended for the characteristics of the general population.

Features of statistical research on selective aggregate:

1. The selective set is formed in such a way as to ensure equal opportunity for all elements of the original set of observation.

2. The selective set must be representative (representative), accurately and fully reflect the phenomenon, i.e. Giving the same idea of \u200b\u200bthe phenomenon as if the entire general aggregate was studied.

Selective aggregate - Part of the general population, selected by a special (selective) method and intended for the characteristics of the general population.

Requirements for selective aggregate:

1) must be representative, accurately and fully reflect the phenomenon, i.e. Giving the same idea of \u200b\u200bthe phenomenon as if the entire general aggregate was studied, for this it should:

but. be sufficient

b. have the main features of the general population (all elements in the selected part must be presented in the same relation as in general)

2) when it is formed, must be observed the basic principle of the formation of selective aggregate: Equal opportunity for each observation unit to get into the study.

Methods for the formation of a statistical aggregate:

1) Random selection is the selection of observation units by draw using a table of random numbers, etc. At the same time, for each unit, an equal opportunity to get into the sample is ensured.

2) mechanical selection - units of the general population, consistently located according to any sign (according to the alphabet, by dates to the doctor, etc.) are divided into equal parts; From each part in a predetermined procedure, each 5, 10 or N-th of the observation unit is taken in such a way as to ensure the necessary sampling.

3) Typical (typological) selection - implies a mandatory preliminary dismemberment of the general population into separate qualitatively homogeneous groups (types), followed by a sample of observation units from each group by subbands of random or mechanical selection.

4) serial (nest, nesting) selection - implies a sample from the general population of non-individual units, but a total series (organized a combination of units of observations, for example, organizations, districts, etc.)

5) Combined methods - a combination of various ways to form a sample.

"

Groupings in criminal law statistics allow you to give the most complete and comprehensive criminological and criminal law characteristics for the most diverse grounds:

• W by type - articles of the Criminal Code
• W on the object of encroachment,
• Sh in territorial sign - district, region, edge, republic,
• W ratio of mercenary and violent crimes
• Sh in the time of committing crimes, etc.),
• The personality of criminals (on the floor, age, education, social situation, place of residence, etc.),
• W causes and conditions that contribute to the commission of crimes, as well as measures of social and legal control over them.

At the same time, various groups from criminal law statistics are very important to compare not only with each other, but also with groups from other branches of statistics (demographic, socio-economic, etc.), reflecting interrelated phenomena.

Differences in targeted grouping, tasks that they solve in statistical analysis are expressed in the existing classification: typological, structural, analytical ones.

The most important task of groupings in statistics is that the mass of units of aggregate is considered to be partitioned into characteristic types, i.e. On groups, homogeneous for essential features. This task is solved using a typological grouping.

Typology Grouping - This is the distinction of the studied aggregate for homogeneous groups, types according to a significant qualitative characteristic.

The main objective of the typological group is the separation of one type of phenomena from another statistical means. This type of groupings is largely determined by the prevailing ideas about which types of phenomena are the content of the studied aggregate.

In legal statistics, these are three types of legal relations: criminal law, administrative and legal and civil laws, which are determined by its sections.

In criminal law statistics, in particular, it may be, for example, the distribution by sex persons who have committed crimes.

This grouping on a high-quality basis, when there are only two meanings of this feature, and one of them eliminates the other, it is called alternative in the statistics.

The sequence of actions of this type of grouping is element:

• 1) the type of phenomenon is determined to be allocated - in our case registered crimes;
• 2) the grouping feature is selected as the basis of the description of the type - in our case, the sex of persons who have committed crimes;
• 3) the boundaries of the intervals are established (in our case, for all persons identified in the commission of crimes);
• 4) The grouping is drawn up in a table, selected groups (based on a combination of grouping signs) are combined into the outlined types and the number (specific weight) of each of them is determined.

In the typological group, that is, when submitting units into high-quality-homogeneous categories, these categories should, as noted, to be determined on the basis of the provisions of the relevant science and norms of the law. For example, a grouping of punishments by type is carried out by criminal law (judicial) statistics in full compliance with Art. 43-59 of the Criminal Code, establishing with an exhaustive fullness of accurate qualitative signs of their individual species (fine, correctional work, imprisonment, etc.

Structural groups - This is the distribution of typically homogeneous groups on quantitative features that may vary (vary). In the scientific literature, this type of groupings are sometimes called variational. With their help, in criminal statistics, it is studied, for example, the structure of criminals according to the varying sign: by age, the number of condoms, in terms of deprivation of freedom, sizes of wages and other quantitative features.

Structural, or variational, grouping statistical data can be carried out in order to study the change in the structure of typically homogeneous groups of crime, offenders, civil lawsuits and other indicators. For the structural grouping of the material, the presence of homogeneous aggregates, dissected by the magnitude of the changing (varying) feature.

If the typological group is based on qualitative signs, the basis of the variations are the quantitative (specific gravity of crimes, persons, affairs, the age of offenders, the period of punishment, the number of condoms, the number of completed classes, the amount of damage, the amount of the claim, the deadlines of the investigation and the consideration of criminal or civil Affairs, etc.).

Quantitative shifts in the structure of studied phenomena in several years indicate a change in objective trends and patterns, investigative or judicial practice, the effectiveness of law enforcement or other legal authorities. Taking, for example, absolute and relative criminal record indicators for many years, we will identify trends in judicial practice and its relationship with real crime. After studying the dynamics of absolute numbers of record crimes of some kind, the dynamics of its specific gravity in the structure of all crime, we discover the trend of the development of this act.

Structural groups can be built on the basis of the equity distribution of crimes on the areas and objects of criminal encroachment, subjects of the federation, regions and territories

Structural differences in this case may disclose the characteristics of the criminological situation in a particular region.

The structural (variational) groupings are adjacent to the rows of distribution of units of aggregate according to variation features.

Analytical groups - This is a dependence distribution, the relationship between two or several heterogeneous groups of phenomena or their signs (for example, the distribution of the theft at the place and the time of their commission; convicts for motor transport crimes - according to the work of the driver, etc.).

Analytical groupings are of great importance for all branches of legal statistics. They make it possible to identify many hidden dependencies and relationships, which is important for making practical solutions and the development of legal science. Analytical potential has other types of groups, as well as other statistical techniques, but the analytical group is directly pursued by the establishment of dependencies between the studied phenomena. By the nature of its tasks, the analytical group is closely facing correlations, when the dependence between the studied phenomena or processes may be relatively measured.

All types of groups reviewed in the analysis of socio-legal, solitological and criminological aspects are usually used together. For example, for the establishment of public dangers and severity of the crimes committed, we can disdate their combination by categories of acts and forms of guilt (typological group). To determine the effectiveness of the fight against crime of various law enforcement agencies (internal affairs, drug control, customs service, prosecutor's office, security services), we can explore the varying of the disclosure of crimes in the mentioned departments (variational group).

In order to establish the causes and conditions of growth or (crime reduction in the city, region, country), a number of analytical groups should be applied.

The subject of statistics changed throughout the history of the development of statistical science, until now, scientists have not come to an unequivocal answer on this issue.

The subject of statistics is the study of public phenomena and their analysis.

So, English statistics, J.E. Yula, M.J. Kendel: "Regardless of which the knowledge of the knowledge, numeric data is obtained, they have a certain kind of properties, to identify whose special kind of scientific processing method may need. The latter is known as a statistical method or statistics. "

The versatility of statistics as science is related to the fact that it is engaged in the methods of measurement and interpretation, both in the public sciences and in the sciences of nature. Statistics recognize a special method used in various fields of activity, when solving a variety of tasks, defined as "collecting, presenting and interpreting numerical data".

Statistical methodology and practice are inextricably linked, complement and develop each other. Statistical theory summarizes the experience of practical work, develops new ideas and methods enriching practical statistical activities. Statistical practice is scientifically organized work.

In this way, statistics - Science, which studies the quantitative side of mass social phenomena in order to establish patterns in an inextricable connection with their qualitative side in specific conditions of place and time in their relationship and interdependence (N.N. Ryuzovsky "General statistical theory").

The essence of this definition is associated with six main moments:

1. Not all phenomena are studied, but only public and socio-economic. These phenomena are complex, diverse (for example: production work, healthcare, cultural activity, population, etc.), differ from nature phenomena, which have a relatively stable nature and repeatability over time.

2. The mass socio-economic phenomena is investigated, and not single, since the patterns of development are manifested through many facts, when generalizing data with a sufficiently large number of units (the law of large numbers).

3. The phenomena gives a quantitative assessment, on the basis of which their high-quality content is revealed (for example: for quantitative analysis of unemployment, the employment rate and the unemployment rate is applied).

4. The numeric characteristics of the same phenomenon are different in space and in time.

5. Socio-economic phenomena are studied in dynamics in order to identify trends and the development of development, forecast of future situations.

6. Studying phenomena in relationships and interdependence.

Thus, when using statistical methods, it is important to remember the unity of the quantitative and high-quality sides of the phenomenon under study.

So, statistics are engaged in the study of mass phenomena or aggregates.

Total - is a homogeneous on any sign of a group that consists of a nucleus and its surrounding phenomena ("layer"). The core is the concentrated expression of all the specific properties of this group, distinguishing one combination of others. "Layer" - units with an incomplete set of specific properties that belong to a given population with a certain probability.

For example: A set - students, among students there are:

- "The perfect student" is perfectly learning, it reads a lot, actively participates in extracurricular work - this is the core.

A student for whom only "interesting", special knowledge; - This is one layer.

A student who is interesting only extracurricular life, etc. - This is another layer.

Thus, the "quality" of some students can practically be accurately attributed to one or another type, others are quite difficult.

The ratio of the nucleus and its surroundings in different sets is different, and depends on the conditions of the existence of a combination: duration, stability, interaction with other aggregates, etc. However, the kernel should be most of the combination units, as it determines its characteristic features.

Since statistics are engaged in studying phenomena at a particular point and time - it has a limited number of data.

Statistical aggregate - These are a set of objectively existing units of the studied phenomenon, combined with a single qualitative basis, a common bond, but differ from each other by individual features. (For example, a set of households, a combination of families, a totality of enterprises, firms, associations, etc.).

The aggregate must be distinguished from the system and structure, because in the aggregate there is no orderly, here all the elements are separated.

Sign - This is a qualitative feature of a unit of aggregate.

By the nature of the display of the properties of the units studied the set, signs are divided into two main groups:

1. Quantitative - signs that have direct quantitative expression, That is, they can be folded (for example: age, income, number of children, number of years of learning, work experience, etc.). Support the relationship "more is less."

2. Qualitative - signs that do not have direct quantitative expression, that is Signs that cannot be folded (for example: Paul, profession, the nature of labor, attitude to anything). Inappropriate relations of "inequality equality". (! Do not allow relationships more or less.)

All high-quality signs are divided into:

Attributes are a feature of this phenomenon (for example: profession, occupational nature, etc.)

Alternatives - opposite options (for example: products are suitable or corrupted, for representatives of individual age groups there is a chance to live or not to live to the next age group; each person may be married or not, a man or a woman, etc.).

In addition, signs in statistics can be divided into different groups, depending on the basis. The main classifications of the signs are presented in Figure 1.2.

Classification of signs in statistics

Descriptive - Signs expressed verbel (Form of ownership of the enterprise, type of used raw materials, profession, etc.) Descriptive features are divided into nominal, which cannot be streamlined, rank (nationality, industry affiliation of the enterprise, etc.) and ordinal, which can be ranked (tariff discharge , student performance score, company ratings, etc.).

Quantitative Signs - such, whose individual values \u200b\u200bhave a numerical expression (area of \u200b\u200bthe territory of the region, the cost of the company's funds, the price of goods, etc.).

Primary Signs characterize the unit of aggregate as a whole. They can be measured, counted, weighed and exist by themselves regardless of their statistical study (the number of residents of the city, gross grain collection, the amount of insurance payments).

Secondary Symptoms are calculated by the ratio of primary signs. Secondary signs are products of human consciousness, the results of the learning of the object being studied.

Straight Signs - properties inherent in the object that they are characterized.

Indirect Signs - Properties inherent in the most studied object, and other aggregates relating to the object.

Alternative Signs - those that take only the bottom of the value (half of a person, place of residence (city-village), signs of possessions or necessitating something.

Discrete Signs. There are only integer values.

Continuous Signs - capable of taking any values, both and fractional. Continuous include all secondary signs.

Momentny Signs - characteristics of the state, the presence of something at a certain point in time.

Interval Signs - process characteristics for a certain period of time: year, half, quarter, month, day, etc.

A feature of a statistical study is that only varying signs are being studied in it, i.e. Signs receiving various values \u200b\u200b(for attribute, alternative signs) or having different quantitative levels in individual units of aggregate.

The significant property of the statistical aggregate is variation.

Variation - This is the property of a statistical aggregate, reflecting the ability to change, due to both external and internal factors, as associated with the essence of the object under study, and not related to it.

Statistical pattern - This is a pattern established by the law of large numbers in massive varying phenomena combined into a statistical aggregate.

Statistical patterns are manifested in trends.

Statistics features:

1. Descriptive - with the help of numbers and numbers is given the characteristics of a particular situation, process, phenomena

2. Explanatory - caused causal relations between phenomena and processes; Factors cause certain links.

The nature of statistical data is due to 3 main properties:

1. Uncertainty of statistical data

2. The probabilistic nature of statistical data (a sign can take this value, and may not accept)

3. Abstract statistical data.

Eliseeva I.I. Workshop on the general theory of statistics. M.: Finance and Statistics, 2008. p.8.