# STATISTICS IN ECONOMICS

### STATISTICS IN ECONOMICS

Statistics are numerical statement of facts capable of analysis and interpretation as well as study of the methods used in collection, organization, presentation, analysis and interpretation of numerical data.

Statistics word has been derived from

Latin word ‘Status

Italian word ‘Statista

German word ‘Statistik

French word ‘Statistique’.

GOTT FREID ACHENWALL is known as FATHER OF STATISTICS. He was the first to use this term in 1749.

RA FISHER regards the science of statistics as ‘Mathematics of observational data.

It has been defined in two senses:

• SINGULAR SENSE
• PLURAL SENSE

### STATISTICS IN PLURAL SENSE

It refers to group of numerical data collected in a systematic manner with some definite objective.

EXAMPLE: Number of persons suffering from malaria in different localities of the city.

ACCORDING TO HORACE SACRIST

“Statistics is the aggregate of facts, affected to a marked extent by multiplicity of causes, numerically expressed, enumerated or estimated according to a reasonable standard of accuracy, collected in a systematic manner, for a predetermined purpose and placed in relation to each other”.

The features of statistics in plural sense are as follows:

STATISTICS ARE AGGREGATE OF FACTS

These are the aggregate of facts i.e. set of figures. It means no isolated or single figure can be called as statistics.

EXAMPLE: Marks of a student in a class cannot be termed as statistics. The marks of all the students of the class is termed as statistics.

STATISTICS ARE AFFECTED TO MARKED EXTENT BY MULTIPLICITY OF CAUSES

These are aggregate of facts which are affected by various factors not a single factor alone. The variety of factors affect the data collected.

EXAMPLE: The production of wheat is affected by various factors like technique used for cultivation of crop, quality of pesticides and insecticides used, fertility of the soil, rainfall etc.

STATISTICS ARE NUMERICALLY EXPRESSED

Only that set of figures can be called as statistics that is capable of being expressed in numerical form. It means the variable like honesty, integrity, intelligence cannot be called as statistics. Thus, statistics mean quantitative data not qualitative data.

EXAMPLE: Ram is tall and sham is short is qualitative data, hence not called statistics. But the height of Ram is 5 Ft and sham is 4 ft is quantitative data and will be known as statistics.

STATISTICS ARE ENUMERATED OR ESTIMATED ACCORDING TO REASONABLE STANDARD OF ACCURACY

Statistics in the form of numerical data can be obtained by two ways i.e. by enumeration or by estimation.

Enumeration method is also known as census method. This method is applied in case there is small amount of data available i.e. field of enquiry is not too vast. The data collected by this method is very much reliable and correct.

Estimation method is also known as Sampling method. When the field of enquiry is very vast and there is large amount of data to be studied, then this method is used.  As per this method, a sub-part known as sample is collected from the whole population and the conclusions are found out for the whole universe on the basis of sample selected.

STATISTICS SHOULD BE COLLECTED IN SYSTEMATIC MANNER

Before collecting the data, a framework should be decided. The data must be collected in a systematic manner to ensure the success of the enquiry. The data collected in haphazard manner will serve no purpose.

STATISTICS SHOULD BE COLLECTED FOR PRE-DETERMINED PURPOSE

Before collecting the data for the enquiry, the purpose of the enquiry should be determined in advance. The purpose of enquiry, the proposed sources of data must be kept in mind before conducting the enquiry. The investigator should understand each element of the topic before making any kind of investigation.

STATISTICS SHOULD BE PLACED IN RELATION TO EACH OTHER

Statistics should be capable of being compared with the data of the same category. All the data collected must be of homogenous nature to make the comparison easy.

EXAMPLE: It makes no sense to compare the height of a man with the height of an animal.

### STATISTICS IN SINGULAR SENSE

In singular sense, statistics refers to a science of all those statistical methods and techniques which are related with various stages of statistical analysis.

ACCORDING TO CROXTON AND COWDEN

“Statistics may be defined as the science of collection, presentation, analysis, interpretation of numerical data.”

AL BOWLEY defines statistics as ‘Science of Counting’.

The features of statistics in singular sense are as follows:

COLLECTION OF DATA

Collection of data is the first step in the statistical investigation. Data must be collected in a systematic way by keeping purpose in mind. If the data collected is faulty, the conclusions drawn will be wrong. The data is of two types:

• PRIMARY DATA
• SECONDARY DATA

Primary data is the data collected for the first time and used specially for the particular problem. This is also known as original data.

Secondary data is that data which has been already collected for some other study and can be obtained from published sources also.

ORGANISATION OF DATA

In the second stage of statistical investigation, the data collected is organized. Organisation of data involves

• Editing of data
• Classification of data
• Tabulation of data

Editing of data is done to remove the unnecessary elements and inconsistencies.

Classification of data is done to arrange the similar nature of data in a group.

Tabulation of data means presentation of data in rows and columns.

PRESENTATION OF DATA

After the collection of data, the data is presented in the form of tables, charts, bar graphs, histograms, pie-charts, diagrams etc. this is done to make the data available in the easy form so that it can be understood even by the layman.

ANALYSIS OF DATA

Analysis of data refers to understanding and establishing relationship among the different variables of the data. The data is analysed with the use of:

• Measures of Central Tendency
• Correlation analysis
• Regression analysis
• Measures of Dispersion
• Time series analysis
• Theory of probability
• Index Numbers
• Skewness
• Measure of Kurtosis
• Interpolation and extrapolation, etc.

INTERPRETATION OF DATA

This is the last stage in the statistical investigation. Interpretation of data means drawing the conclusions or results from the data analysed. This is the most difficult task. A good interpretation of the data depends upon the skills, ability, knowledge and experience of the investigator. If the results of the analysed data are not properly interpreted, the whole statistical investigation will go waste.