The result of the analysis of processes and phenomena investigated using statistical methods is a set of numerical characteristics that can be classified into absolute and relative indicators.
Absolute indicators
Absolute values from the point of view of statistics represent the number of units or amounts in the sample, which are a direct result of the summary and grouping of the analyzed data. Absolute indicators reflect, so to speak, the “physical” characteristics of the studied processes and phenomena (area, mass, volume, spatio-temporal parameters), which, as a rule, are recorded in primary accounting documents. Absolute values always have a dimension. We also note that, in contrast to the mathematical interpretation, the statistical absolute value can be both positive and negative.
Classification of absolute indicators
Absolute values are classified by the method of representing the sizes of the studied phenomena into individual, group and general.
Individual indicators include absolute indicators expressing the numerical sizes of individual units of the population. For example, the number of employees in the organization, gross output of the enterprise, profit, etc.
Group indicators are called parameters that define dimensional characteristics or the number of units in a certain part of the population. Such indicators are calculated by summing the corresponding absolute parameters of the individual units of the study group or by directly calculating the number of units in the sample from the general population.
Absolute indicators describing the size of the characteristic for all units of the population are called general . Such parameters are the result of a summary of the results of statistical studies. Such indicators include the wages fund of enterprises in the region, the gross yield of wheat in the state, etc.
Relative value
From the point of view of statistics, a relative value is a generalizing parameter that describes the quantitative ratio of two absolute values. In other words, relative indicators characterize the interconnections and interdependencies of two compared absolute parameters.
The use of relative values in socioeconomic research
Relative indicators play an important role in the analysis of socio-economic processes, since the absolute characteristics themselves do not always allow a correct assessment of the analyzed phenomenon. Often their true significance is manifested only during comparison with another absolute indicator.
Relative indicators include parameters that determine the structure of the phenomenon, as well as its development over time. With their help, it is easier to trace the development trends of the investigated process and to make a forecast of its further evolution.
The main feature of relative values is that they allow a comparative analysis of processes incomparable in absolute units, which, in turn, opens up opportunities for comparing the levels of development or prevalence of various social phenomena.
The principle of calculating the relative value
Relative to absolute indicators, which are input data for statistical analysis, relative values are derived from them, or secondary. The calculation of relative indicators in general is performed by dividing one absolute parameter by another. In this case, the value in the numerator is called the compared, or the current, and the indicator located in the denominator with which the comparison is made is the basis (base) of the comparison.
Obviously, it is possible to make a comparison even of seemingly completely unrelated absolute values. Relative indicators necessary for statistical analysis should be selected based on the objectives of a specific study and the nature of the available primary data. In this case, it is necessary to be guided by the principles of visibility and ease of perception.
As current and basic indicators for the calculation, you can use not only absolute, but also relative characteristics. Relative parameters obtained by comparing the absolute characteristics are called first-order indicators, and relative parameters are called higher-order indicators.
Dimensions of Relative Values
Statistical analysis allows you to perform calculations of relative indicators for both homonymous and unlike variables. The result of the comparison of the parameters of the same name are unnamed relative values, which can be expressed in multiplicity coefficients, representing how many times the current indicator is more or less than the base indicator (in this case, the basis of comparison is one). Often, in statistical studies, the comparison base is taken equal to 100. In this case, the dimension of the obtained relative indicators will be percent (%).
When comparing the opposite parameters, the ratio of the corresponding dimensions of the indicators in the numerator and the denominator is taken as the dimension of the obtained relative value (for example, the indicator of the level of GDP per capita has a dimension of million rubles / person).
Classification of Relative Values
Among the variety of relative parameters, the following types are distinguished:
- indicator of dynamics;
- indicators of the plan and plan implementation;
- intensity indicator;
- indicator of structure;
- coordination indicator;
- comparison indicator.
Dynamics indicator (OPD)
This parameter describes the ratio of the current level of development of the investigated phenomenon to a certain level of its development in the previous period, taken as a base. Expressed as a multiple ratio, the relative indicator of dynamics is called the growth rate, and in percentage - the growth rate.
Indicators of the plan (OPP) and implementation of the plan (PPR)
Similar indicators are used by all economic entities involved in current and strategic planning. Calculate them as follows:
The characteristics considered above are related by the following relationship:
OPD = OPP * OPRP.
The relative indicator of the plan determines the intensity of the task compared to the previous period, and the implementation of the plan - the degree of its implementation.
Structure Index (OPS)
This relative indicator shows the structural composition of the population and is expressed in relation to the size of the absolute feature of the structural part of the studied object to the size of the feature of the population as a whole. In other words, the calculation of structure indicators consists in calculating the specific gravity of each part of the population:
OPS are usually expressed as fractions of a unit (coefficients) or percent. The sum of the specific gravities of the structural parts of the studied population in this case should be equal to one or one hundred percent, respectively.
Such coefficients are used to study the structure of multicomponent complex phenomena, for example, when studying emissions of harmful substances by vehicles in a traffic stream, dividing them by the type of fuel used (gasoline, diesel, gas) or by purpose (cars, trucks, buses), etc.
Coordination Indicator (MIC)
Such a parameter characterizes the ratio of the characteristics of some part of the statistical population to the characteristics of the base part. The relative indicator of coordination is used in statistical analysis to more clearly represent the relationship between the individual parts of the studied population.
As the base, choose the part of the population with the maximum specific gravity or which is a priority.
Intensity Index (OPI)
This characteristic is used to describe the distribution of the investigated phenomenon (process) in its environment. Its essence lies in comparing unlike, related in some way quantities.
An example is indicators of the level of GDP per capita, demographic indicators of natural increase (decrease) in the population per 1000 (10000) people, etc.
Comparison Index (OPSr)
This parameter describes the ratio of the same absolute characteristics of different objects:
A relative comparison indicator can be used for comparative analysis, for example, the population of different countries, prices for identical goods of different brands, labor productivity in different enterprises, etc.
The calculation of relative characteristics is an important stage of statistical analysis, however, considering them regardless of primary absolute indicators, we can come to unreliable conclusions. Therefore, a correct assessment of various socioeconomic processes and phenomena should be based on a system of parameters, which includes both absolute and relative indicators.