FUNCTIONS OF STATISTICS

 Let us now discuss some of the important functions of statistics:

 

1) To present facts in a proper form: Statistical methods present general statements in a precise and definite form. For example, you may say that in India average yield of cotton per hectare is 180 Kg. This statement is more precise and convincing than saying that the average yield of cotton in India is very low.

 


2) To simplify unwieldy and complex data: Statistical methods simplify unwieldy and complex data to make them understandable easily. The raw data is often unintelligible. One cannot grasp their characteristics unless the data is classified according to some common characteristics, Suppose, you are given the weekly wages of 1,000 workers in a factory. You will not be in a position to draw any inference from the data unless they are condensed through classification such as the following:

 

Weekly Wages (Rs.)  

No. of Workers

Below-600    

100

600-700    

200

700-800   

400

800-900   

200

Above 900    

100

Total     

1000

 

3) To provide techniques for making comparison: The primary purpose of statistics is to facilitate a comparative study of different phenomena either over time or space, For instance, the estimation of national income is not done for its own sake. But it is done to compare the income over time to get an idea whether the standard of living of people is rising or not. Suppose, as compared to 2005, the per-capita income in India has increased by 10% in 2005. On the basis of this information, we shall be in a position to throw some light on the standard of living of an Indian in 2006.

 

4) To study relationship between different phenomena: Statistical measures such as correlation and regression are used to study relationships between variables. Such relationships are important for making decisions. For instance, you may find a relationship between the demand of a product and its, prices. In general, if the prices rise, the demand for the product is likely to decline.

 

5) To forecast future values: Some of the statistical techniques are used for forecasting future values of a variable. O n the basis of sales figures of the last 10 years, a marketing manager can estimate the likely demand for his product during the next year.

 

6) To measure uncertainty: With the help of probability theory, you can measure the chance of occurrence of uncertain event. Probability concepts are quite useful in decision-making. Suppose, if you are interested in estimating the chance of your passing the B.Com examination, you may get an idea about it by studying the pass percentages of students during the last 10 years.

 

7) To test a hypothesis: Statistical methods are extremely useful in formulating and testing hypotheses and for the development of new theories. For instance, a company is desirous of knowing the effectiveness of its new drug to control malaria. It could do so by using a statistical technique called Chi-square Test.

 

8) To draw valid inferences: Statistical methods are also useful in drawing inferences regarding the characteristics of the universe (population) on the basis of sample data.

 

9) To formulate policies in different fields: Statistical methods are very useful in formulating various policies in social, economic, and business fields. The Government, for instance, utilises vital statistical data for formulating family planning programme. Similarly, the government utilises the information on consumer price indices for granting dearness allowance to its employees.

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