Statistical data can be presented in the form of statistical tables, statistical graphs and statistical charts.

Statistical tables are drawn up as a result of the summary and grouping of available data from the observation. Statistical tables necessarily contain totals and consist of a subject and a predicate.

Subject table shows what the table is about, it is located on the left and represents the contents of the rows.

Predictable tables located at the top and represents the content of the graph. The predicate shows what features the subject is characterized by.

Statistical graphs. Statistical graphing is the final step in summarizing and grouping statistical data. Graphical representation is the most effective form of presentation of statistical data in terms of their perception.

Schedule is called a conditional, visual representation of statistical quantities and their ratios using geometric lines and figures.

Each graph must include the following elements: a symbol, a graph field, scale reference points, and a coordinate system.

Graphic image - geometric signs, a set of points, lines, figures, with the help of which statistical quantities are depicted.

Graph field represents the space in which geometric signs are placed.

The scale reference points of the statistical graph are determined by the scale and scale.

Statistical Plot Scale - it is a measure of converting a numerical value into a graphic one,

Scale scale - a line whose specific points can be read as specific numbers. The scale consists of a line (scale carrier) and a number of points marked on it, arranged in a certain order.

Uniform scale is the length of a segment taken as a unit and measured in any measures.

A coordinate system is required to place geometric symbols in the plot field. The most common system of rectangular coordinates.

According to the method of construction, graphs are divided into line graphs, diagrams, cartograms, cartodiagrams.

The class of line graphs includes: polygon, cumulative and Lorentz curve.

Polygon called the broken line, the segments of which connect the points X and / j (X j - attribute value; - frequency).

The polygon is used for a discrete distribution series.

Cumulata - polyline, compiled by the accumulated frequencies or parts, the coordinates of the points of which are X ( and f. (X j - the value of the feature, for an interval series - the upper limit of values (X.); / (- accumulated frequency).

The starting point of the polyline of the interval distribution series is the lower boundary of the value ( X") in the first group.

Lorentz curve, or concentration curve, called the curve of the relative concentration of the total value of the trait. It is a broken line, the coordinates of the points of which on the abscissa axis are the accumulated relative frequencies, and on the ordinate axis - the accumulated (cumulative total) value of the feature X j.

The closer the Lorentz curve is to a straight line, the more uniform the distribution of the feature, i.e. concentration is less. The greater the curvature of the curve, the more uneven the distribution, i.e. concentration is greater.

Statistical charts. The class of charts, first of all, includes a histogram (bar chart), as well as bar, strip, pie, linear, square, sector, curly, etc.

Bar chart - it is a stepped shape made up of rectangles whose bases are equal to the spacing in the group, and the heights are the density in the group (absolute or relative).

When constructing bar charts, data are displayed in the form of bars of the same width, but different heights, depending on the numerical values \u200b\u200bof the displayed quantities at a certain scale.

A variety of bar charts are strip and bar charts. They depict the dimensions of the feature in the form of horizontally located rectangles of the same width, but different lengths, in proportion to the displayed values. The beginning of the stripes must be on the same vertical line.

Pie charts it is convenient to use to depict the structure of a phenomenon, in this case the circle is divided into sectors proportional to the fractions of parts of the phenomena. The circle is taken as a whole (100%) and divided into sectors, the arcs of which are proportional

the values \u200b\u200bof the individual parts of the displayed quantities. The arc of each sector (or the value of the central angle) is determined by the formula

where 360 \u200b\u200b° is the area of \u200b\u200bthe circle;

d - specific gravity of the depicted phenomenon as a percentage.

If the statistical data are presented in absolute terms, then the formula for determining the arc takes the form:

where b - the magnitude of the displayed phenomenon in absolute terms.

For building circular and square charts it is necessary to carry out preliminary calculations, since the available statistical data (/)) correspond to the areas of geometric figures (circles or squares).

To build a circle, you need to find the radius of the circle using the formula

To build a square, you need to find the side of the square, based on the formula for the area of \u200b\u200ba square:

Barbarian sign used for a visual characteristic of three interrelated quantities - this is a rectangle in which the base is one indicator, the height is another, and the product of the base by the height characterizes the value of the derivative of the third indicator.

Curly charts are constructed in two ways: the compared statistical values \u200b\u200b(/)) are depicted by figures - symbols of different sizes in proportion to the volumes of these populations, or by different numbers of identical signs-symbols, each of which is assigned a certain numerical value.

For a graphical representation of the spatial distribution of a statistical indicator, cartograms are used, which are background and point.

Cartogram is a combination of a chart with a geographic map.

On the background cartograms, the distribution of the studied phenomenon over the territory is depicted by various colorings of the territory.

units with different color density or shading of different intensity.

On a point cartogram, the symbols of the graphic representation of statistical data are points located within certain territorial units. Each point is assigned a specific numerical value.

A cartogram is used in cases when it becomes necessary to show the territorial distribution of any one statistical feature in aggregate to identify the pattern of distribution of this feature.

Automated ways of building charts. In an automated way, charts can be created based on case data generated and grouped in a table. To provide a clear diagram, the data block must meet certain requirements:

• data should be systematized by quantity and by groups, columns and rows;
• data for different categories should be comparable;
• headings of tables, rows, columns should be short and clear so as not to take up much space and to provide a correct understanding of the values \u200b\u200bof the constructed diagram;
• data must be located in one or more rectangular ranges with text labels in the top row and left column.

As part of an integrated package Microsoft Office spreadsheet information is processed by the program Microsoft Excel. A spreadsheet is the computer equivalent of a regular spreadsheet.

Table processor - a special program (software package) that processes information presented in tabular form.

Microsoft Excel defines the first row of data, starting with the first cell in the upper-left corner of an existing non-date selected data range, and ending with the remaining selected rows and columns.

To build diagrams in a spreadsheet processor, a special diagramming wizard is provided using a plotter Microsoft Graph. The charting wizard is launched by clicking on the icon in the standard toolbar. As a preliminary, it is recommended to select the range of cells containing the data used for charting. Diagrams are built in four stages:

• 1) choice of type and type of diagram;
• 2) clarification of the range of data and the arrangement of rows in rows or columns. The result of plotting a diagram when positioned

the rows in rows and columns can vary significantly. By default, the window displays a chart view for the selected range of cells. If you have not previously selected the data, you must do this in this window by clicking on the icon of the stylized table in the field Range and highlighting the data in the table. Tab "row" allows you to add and remove rows, indicate the ranges in which the corresponding rows are presented, labels of the category axis;

• 3) specifying the title of the diagram and making the necessary signatures;
• 4) placement of the diagram on the sheet of the spreadsheet processor (on the current or separate worksheet).

To edit the elements of the diagram, you need to double-click, after which you will go to the corresponding window for changing the parameters of the selected element. A significant help is provided by the context-sensitive menu, called on individual elements of the diagram.

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

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

Statistics develops a special methodology for research and processing of materials: mass statistical observations, the method of groupings, average values, indices, balance method, method of graphic images.

Methodological features is the study of: the mass character of phenomena, qualitatively homogeneous signs of this or that phenomenon in dynamics.

Statistics include a number sections, among which: general theory of statistics, economic statistics, branch statistics - industrial, agriculture, transport, medical.

11. Groups of indicators for assessing the health status of the population.

Population health is characterized by three groups of key indicators:

A) medical and demographic - reflect the state and dynamics of demographic processes:

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

Population dynamics (mechanical emigration and immigration, natural fertility, mortality, natural increase.)

Marital status (marriage rate, divorce rate, average length of marriage.)

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

Life expectancy

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

B) indicators of morbidity and traumatism (primary morbidity, prevalence, accumulated morbidity, pathological affection, health index, mortality, traumatism, disability.)

C) indicators of physical development:

Anthropometric (height, body weight, chest circumference, head, shoulder, forearm, lower leg, thigh)

Physiometric (lung capacity, hand muscle strength, back strength)

Somatoscopic (physique, development of muscles, degree of fatness, shape of the chest, shape of legs, feet, severity of secondary sexual characteristics.)

Medical statistics, its sections, tasks. The role of the statistical method in the study of public health and the performance of the health care system.

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

There are 3 sections of medical statistics:

1. Population 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 size and composition of the population, its reproduction, natural movement, physical development, the prevalence of various diseases, life expectancy, etc.). The assessment of health indicators is carried out in comparison with generally accepted estimated levels and levels obtained in different regions and in dynamics.

2. Health statistics - solves the issues of collection, processing and analysis of information about the network of health care institutions (their location, equipment, activities) and personnel (about the number of doctors, middle and junior medical personnel, about their distribution by specialties, work experience, about their retraining, etc. .). When analyzing the activities of medical and preventive institutions, the data obtained are compared with the standard levels, as well as the levels obtained in other regions and in dynamics.

3. Clinical statistics - is the use of statistical methods when processing the results of clinical, experimental and laboratory studies; it allows one to quantitatively assess the reliability of the research results and solve a number of other problems (determining the volume of the required number of observations in a sample study, forming an experimental and control group, studying the presence of correlations and regression links, eliminating the qualitative heterogeneity of groups, etc.).

The tasks of medical statistics are:

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

2) identification of links between health indicators and various factors of the natural and social environment, assessment of the influence of these factors on the levels of health of the population.

3) study materially - technical base of health care.

4) analysis of the activities of medical institutions.

5) assessment of the effectiveness (medical, social, economic) of medical, preventive, anti-epidemic measures and health care in general.

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

Medical statistics is a method of social diagnostics, since it makes it possible to assess the health status of the population of a country, region and, on this basis, to develop measures aimed at improving public health. The most important principle of statistics is to apply it to study not separate, isolated, but massive phenomena, in order to identify their general patterns. These patterns appear, as a rule, in the mass of observations, that is, in the study of the statistical population.

In medicine, statistics is the leading method, because:

1) allows you to quantitatively measure the health indicators of the population and the performance indicators of medical institutions

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

3) determines the effectiveness of treatment and health measures

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

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

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

The object of any statistical study is a statistical population.

Statistical population - a group consisting of a set of relatively homogeneous elements taken together within the known boundaries of space and time and possessing signs of similarity and difference.

Population properties: 1) homogeneity of observation units 2) certain boundaries of 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 as a whole or its separate groups, the sick, the deceased, those born), medical institutions, etc.

There are two types of statistical population :

a) general population

b) sample population

1. the sample population is formed in such a way as to provide an equal opportunity for all elements of the original population to be covered by observation.

2. The sample must be representative (representative), accurately and fully reflect the phenomenon, i.e. give the same idea of \u200b\u200bthe phenomenon as if the entire population was studied.

Sample population

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

and. be sufficient in number

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

2) during its formation, it must be observed

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

2) mechanical selection - units of the general population, sequentially located according to some criterion (alphabetically, according to the dates of the visit to the doctor, etc.), are divided into equal parts; from each part in a predetermined order, each 5, 10 or n-th observation unit is selected so as to provide the required sample size.

3) typical (typological) selection - presupposes a mandatory preliminary division of the general population into separate qualitatively homogeneous groups (types), followed by sampling of observation units from each group according to the principles of random or mechanical selection.

4) serial (nested, nested) selection - involves sampling from the general population not of individual units, but of whole series (an organized set of observation units, for example, organizations, districts, etc.)

5) to combinedways - a combination of different ways of forming a sample.

Sample set, requirements for it. Principles and methods of forming the sample.

There are two types of statistical population :

a) general population - a set consisting of all observation units that can be attributed to it in accordance with the purpose of the study. When studying public health, the general population is often considered within specific territorial boundaries or may be limited by other characteristics (gender, age, etc.), depending on the purpose of the study.

b) sample population - a part of the general population, selected by a special (sample) method and intended to characterize the general population.

Features of conducting a statistical study on a sample population:

1. the sample population is formed in such a way as to provide an equal opportunity for all elements of the original population to be covered by observation.

2. The sample must be representative (representative), accurately and fully reflect the phenomenon, i.e. give the same idea of \u200b\u200bthe phenomenon as if the entire population was studied.

Sample population - a part of the general population selected by a special (sample) method and intended to characterize the general population.

Requirements for the sample:

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

and. be sufficient in number

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

2) during its formation, it must be observed the basic principle of the formation of the sample: equal opportunity for each observation unit to get into the study.

Methods for forming a statistical population:

1) random selection - selection of observation units by drawing lots using a table of random numbers, etc. In this case, for each unit, an equal opportunity to get into the sample is provided.

2) mechanical selection - units of the general population, sequentially located according to any criterion (alphabetically, according to the dates of the visit to the doctor, etc.), are divided into equal parts; from each part in a predetermined order, each 5, 10 or n-th observation unit is selected so as to provide the required sample size.

3) typical (typological) selection - presupposes the obligatory preliminary division of the general population into separate qualitatively homogeneous groups (types), followed by sampling of observation units from each group according to the principles of random or mechanical selection.

4) serial (nested, nested) selection - involves sampling from the general population not of individual units, but of whole series (an organized set of observation units, for example, organizations, districts, etc.)

5) combined methods - a combination of various methods of forming a sample.

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The activity of people in many cases involves working with data, and it, in turn, can imply not only manipulating them, but also their study, processing and analysis. For example, when you need to condense information, find some relationships or define structures. And just for analytics in this case it is very convenient to use not only, but also to apply statistical methods.

A feature of the methods of statistical analysis is their complexity, due to the variety of forms of statistical patterns, as well as the complexity of the process of statistical research. However, we want to talk about exactly such methods that everyone can apply, and do it effectively and with pleasure.

Statistical research can be carried out using the following methods:

• Statistical observation;
• Summary and grouping of statistical observation materials;
• Absolute and relative statistic values;
• Variational series;
• Sample;
• Correlation and regression analysis;
• Rows of dynamics.

Statistical observation

Statistical observation is a systematic, organized and, in most cases, systematic collection of information, aimed mainly at the phenomena of social life. This method is implemented through the registration of predetermined most striking features, the purpose of which is to subsequently obtain the characteristics of the phenomena under study.

Statistical observation must be carried out taking into account some important requirements:

• It should fully cover the studied phenomena;
• The data received must be accurate and reliable;
• The data received should be uniform and easily comparable.

Also, statistical observation can take two forms:

• Reporting is a form of statistical observation where information is sent to specific statistical divisions of organizations, institutions or enterprises. In this case, the data is entered into special reports.
• Specially organized observation is an observation that is organized for a specific purpose in order to obtain information that is not available in the reports, or to clarify and establish the reliability of the information in the reports. This form includes surveys (for example, opinion polls of people), population census, etc.

In addition, a statistical observation can be categorized on the basis of two characteristics: either based on the nature of data recording, or based on the coverage of observation units. The first category includes interviews, documentation and direct observation, while the second includes continuous and non-continuous observation, i.e. selective.

To obtain data using statistical observation, you can use methods such as questioning, correspondent activities, self-calculation (when the observed, for example, fill in the relevant documents themselves), expeditions and reporting.

Summary and grouping of statistical observation materials

Talking about the second method, the first thing to say about the summary. A summary is the process of processing certain singularities that make up the aggregate body of data collected from an observation. If the summary is carried out correctly, a huge amount of single data on individual objects of observation can turn into a whole complex of statistical tables and results. Also, such a study contributes to the definition of common features and patterns of the studied phenomena.

Taking into account the indicators of accuracy and depth of study, a simple and complex summary can be distinguished, but any of them should be based on specific stages:

• A grouping attribute is selected;
• The order of formation of groups is determined;
• A system of indicators is being developed to characterize a group and an object or phenomenon as a whole;
• Layouts of tables are being developed where summary results will be presented.

It is important to note that there are different forms of summary:

• Centralized summary, requiring the transfer of the received primary material to a higher center for subsequent processing;
• Decentralized summary, where data exploration occurs in several steps upward.

The summary can be performed using specialized equipment, for example, using computer software or manually.

As for the grouping, this process is distinguished by the division of the studied data into groups according to characteristics. The features of the tasks set by the statistical analysis affect what kind of grouping will be: typological, structural or analytical. That is why, for summary and grouping, either they resort to the services of narrowly specialized specialists, or they apply.

Absolute and relative statistics

Absolute values \u200b\u200bare considered the very first form of presentation of statistics. With its help, it is possible to impart dimensional characteristics to phenomena, for example, in time, in length, in volume, in area, in mass, etc.

If you want to know about individual absolute statistical values, you can resort to measuring, evaluating, counting or weighing. And if you want to get the totals for the volume, you should use summary and grouping. It should be borne in mind that absolute statistical values \u200b\u200bdiffer in the presence of units of measurement. These units include value, labor and natural.

And the relative values \u200b\u200bexpress quantitative ratios concerning the phenomena of social life. To get them, some quantities are always divided by others. The indicator with which it is compared (this is the denominator) is called the basis of comparison, and the indicator that is compared (this is the numerator) is called the reporting value.

The relative values \u200b\u200bcan be different, depending on their content. For example, there are comparison values, values \u200b\u200bof the level of development, values \u200b\u200bof the intensity of a particular process, values \u200b\u200bof coordination, structure, dynamics, etc. etc.

To study a set of differentiating features, statistical analysis uses averages - generalizing the qualitative characteristics of a set of homogeneous phenomena for some differentiating feature.

An extremely important property of average values \u200b\u200bis that they speak of the values \u200b\u200bof specific features in their entire complex as a single number. Despite the fact that individual units may have a quantitative difference, the average values \u200b\u200bexpress the general values \u200b\u200bcharacteristic of all units of the studied complex. It turns out that with the help of the characteristics of one thing, one can obtain the characteristics of the whole.

It should be borne in mind that one of the most important conditions for the use of average values, if a statistical analysis of social phenomena is carried out, is the homogeneity of their complex, for which the average value needs to be found out. And the formula for its determination will also depend on how the initial data for calculating the average will be presented.

Variational series

In some cases, data on the average values \u200b\u200bof certain studied quantities may not be enough to carry out processing, assessment and in-depth analysis of a phenomenon or process. Then one should take into account the variation or spread of indicators of individual units, which is also an important characteristic of the studied population.

The individual values \u200b\u200bof quantities can be influenced by many factors, and the studied phenomena or processes themselves can be very diverse, i.e. have variation (this variety is the series of variations), the reasons for which should be sought in the essence of what is being studied.

The aforementioned absolute values \u200b\u200bare directly dependent on the units of measurement of attributes, which means they make the process of studying, evaluating and comparing two or more variation series more complicated. And relative indicators need to be calculated as the ratio of absolute and average indicators.

Sample

The meaning of the sampling method (or, more simply, sampling) is that the properties of one part determine the numerical characteristics of the whole (this is called the general population). The main sampling method is internal communication, which unites parts and the whole, the singular and the general.

The sampling method has a number of significant advantages over the others, since due to a decrease in the number of observations, it allows to reduce the amount of work, expended funds and efforts, as well as to successfully obtain data on such processes and phenomena, where it is either impractical or simply impossible to investigate them completely.

The correspondence of the characteristics of the sample to the characteristics of the studied phenomenon or process will depend on a set of conditions, and first of all, on how the sampling method will be implemented in practice. This can be either a systematic selection, proceeding according to a prepared scheme, or non-routine selection, when a sample is made from the general population.

But in all cases, the sampling method must be typical and meet the criteria of objectivity. These requirements must always be met, since the correspondence between the characteristics of the method and the characteristics of what is subjected to statistical analysis will depend on them.

Thus, before processing the sample material, it is necessary to conduct a thorough check of it, thereby getting rid of all unnecessary and secondary. At the same time, when making a sample, it is imperative to bypass any amateur activity. This means that in no case should you select only from seemingly typical options, and discard all others.

An effective and high-quality sample must be drawn objectively, i.e. it must be produced so that any subjective influences and biased motives are excluded. And in order for this condition to be met properly, it is required to resort to the principle of randomization, or, more simply, to the principle of random selection of options from their entire general population.

The presented principle serves as the basis for the theory of the sampling method, and it must be followed whenever it is required to create an effective sample population, and cases of planned selection are no exception here.

Correlation and regression analysis

Correlation analysis and regression analysis are two highly effective methods for analyzing large amounts of data to explore the possible relationship between two or more indicators.

In the case of correlation analysis, the tasks are:

• Measure the tightness of the existing connection of differentiating signs;
• Determine unknown causal relationships;
• Assess the factors most affecting the final attribute.

And in the case of regression analysis, the tasks are as follows:

• Determine the form of communication;
• Establish the degree of influence of independent indicators on the dependent;
• Determine the calculated values \u200b\u200bof the dependent indicator.

To solve all of the above problems, it is almost always necessary to apply both correlation and regression analysis in a complex.

Rows of dynamics

By means of this method of statistical analysis, it is very convenient to determine the intensity or speed with which phenomena develop, to find the tendency of their development, to single out fluctuations, to compare the dynamics of development, to find the relationship of phenomena developing in time.

A series of dynamics is a series in which statistical indicators are sequentially located in time, the changes of which characterize the process of development of the object or phenomenon under study.

The speaker row includes two components:

• The period or point in time associated with the available data;
• Level or statistic.

Together, these components represent two members of a series of dynamics, where the first term (time period) is denoted by the letter "t", and the second (level) by the letter "y"

Based on the duration of time intervals with which the levels are interconnected, the series of dynamics can be momentary and interval. Interval series allow you to add levels to obtain the total value of the periods following one after another, but in instant series there is no such possibility, but this is not required there.

Series of dynamics also exist at equal and different intervals. The essence of the intervals in the moment and interval series is always different. In the first case, the interval is the time interval between the dates to which the data for analysis is linked (it is convenient to use such a series, for example, to determine the number of actions per month, year, etc.). And in the second case - the time period to which the aggregate of generalized data is tied (such a series can be used to determine the quality of the same actions for a month, a year, etc.). The intervals can be equal or different, regardless of the type of row.

Naturally, in order to learn how to correctly apply each of the methods of statistical analysis, it is not enough just to know about them, because, in fact, statistics is a whole science that also requires certain skills and abilities. But to make it easier, you can and should train your thinking and.

For the rest, research, evaluation, processing and analysis of information are very interesting processes. And even in cases where this does not lead to any specific result, during the research, you can learn many interesting things. Statistical analysis has found its application in a huge number of areas of human activity, and you can use it in school, work, business and other areas, including child development and self-education.

Groupings in criminal law statistics allow us to give the most complete and comprehensive criminological and criminal law characteristics on a variety of grounds:

• Ш by types - articles of the Criminal Code,
• Ш on the object of encroachment,
• Ш on a territorial basis - district, region, territory, republic,
• The ratio of selfish and violent crimes,
• Ш according to the time of committing crimes, etc.),
• Личности personality of criminals (by gender, age, education, social status, place of residence, etc.),
• W reasons and conditions conducive to the commission of crimes, as well as measures of social and legal control over them.

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

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

The most important task of groupings in statistics is to subdivide the studied mass of units of the population into characteristic types, i.e. into groups that are homogeneous in terms of essential characteristics. This task is solved using typological grouping.

Typological groupings - this is the delimitation of the studied population into homogeneous groups, types according to an essential qualitative feature.

The main purpose of the typological grouping is to distinguish one type of phenomenon from another by statistical means. This type of grouping is largely determined by the prevailing ideas about what types of phenomena make up the content of the studied population.

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

In criminal - legal statistics, in particular, it can be, for example, the gender distribution of persons who have committed crimes.

This grouping on a qualitative basis, when there are only two values \u200b\u200bof this feature, and one of them excludes the other, is called alternative in statistics.

The sequence of actions for carrying out this type of grouping is elementary:

• 1) the type of phenomenon that should be highlighted is determined - in our case, registered crimes;
• 2) a grouping attribute is selected as the basis for describing the type - in our case, the gender of the persons who 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, the selected groups (based on a combination of grouping characteristics) are combined into the designated types and the number (specific weight) of each of them is determined.

With typological grouping, that is, when summing up units into qualitatively homogeneous categories, these categories should, as noted, be determined on the basis of the provisions of the relevant science and the norms of the law. For example, the grouping of punishments by type is carried out by criminal - legal (judicial) statistics in full accordance with Art. 43-59 of the Criminal Code, establishing with exhaustive completeness the exact qualitative signs of their individual types (fine, correctional labor, imprisonment, etc.)

Structural groupings - this is the distribution of typically homogeneous groups by quantitative characteristics that can change (vary). In the scientific literature, this type of grouping is sometimes called variational. With their help, in criminal law statistics, they study, for example, the structure of criminals according to a varying criterion: by age, number of convictions, terms of imprisonment, salaries and other quantitative characteristics.

Structural, or variational, grouping of statistics can be done to study the change in structure of typically homogeneous groups of crimes, offenders, civil claims, and other indicators. For the structural grouping of material, it is necessary to have homogeneous aggregates, dismembered by the size of the changing (varying) feature.

If the typological grouping is based on qualitative characteristics, then the variation is based on quantitative (specific gravity of crimes, persons, cases, age of offenders, terms of punishment, number of convictions, number of completed classes, amount of damage, amount of claim, terms of investigation and consideration of criminal or civil cases, etc.).

Quantitative shifts in the structure of the phenomena under study over several years indicate a change in objective trends and patterns, investigative or judicial practice, and the performance of law enforcement or other legal bodies. Taking, for example, the absolute and relative indicators of convictions over many years, we will identify trends in judicial practice and its relationship with real crime. Having studied the dynamics of the absolute numbers of recorded crimes of a certain type, the dynamics of its share in the structure of all crime, we will find trends in the development of this act.

Structural groupings can be built on the basis of the share distribution of crimes by spheres and objects of criminal encroachment, subjects of the Federation, regions and territories

Structural differences in this case may reveal the peculiarities of the criminological situation in a particular region.

Structural (variation) groupings are adjoined by the distribution series of the units of the population according to varying characteristics.

Analytical groups - this is the distribution by dependence, the relationship between two or more heterogeneous groups of phenomena or their signs (for example, the distribution of thefts by place and time of their commission; convicted of road transport crimes - by the length of service 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 interrelationships, which is important for making practical decisions and developing legal science. Other types of groupings, as well as other statistical techniques, have analytical potential, but the analytical group itself directly pursues the establishment of dependencies between the phenomena under study. By the nature of their tasks, the analytical grouping is close to correlation groupings, when the relationship between the investigated phenomena or processes can be relatively accurately measured.

All types of considered groups in the analysis of socio-legal, tortological and criminological aspects, as a rule, are applied together. For example, in order to establish the public danger and the severity of the crimes committed, we can divide their totality into categories of acts and forms of guilt (typological grouping). To determine the effectiveness of the fight against crime of various law enforcement agencies (internal affairs, drug control, customs service, prosecutor's office, security service), we can investigate the variation in the resolution of crimes in the aforementioned departments (variation grouping).

In order to establish the reasons and conditions for the growth or (decrease in crime in a city, region, country), a number of analytical groups should be used.