DEFINITION OF STATISTICS
It deals with classification, tabulation and analysis of numerical facts. Different statistician defined this aspect of statistics in different ways. For example.
A. L. Bowley gave several definitions of Statistics:
i) “Statistics may be called the science of counting” . This definition emphasises enumeration aspect only.
ii) In another definition he describes it as “ Statistics may rightly be called the science of average”.
iii) At another place Statistics is defined as, “Statistics is the science of measurement of social organism regarded as a whole in all its manifestations”.
All three definitions given by Bowely seem to be inadequate because these do not include all aspects of statistics.
According to Selligman “Statistics is the science which deals with the methods of collecting, classifying, presenting , comparing and interpreting numerical data collected to throw some light on any sphere of enquiry”.
Croxton and Cowden defined “statistics as the collection , presentation, analysis ,and interpretation of numerical data”.
Among all the definitions , the one given by Croxton and Cowden is considered to be most appropriate as it covers all aspects and field of statistics.
These aspects are given below:
Collection of Data : Once the nature of study is decided , it becomes essential to collect information in form of data about the issues of the study. Therefore, the collection of data is the first basic step. Data may be collected either from primary source or secondary or from both the sources depending upon the objective/s of the investigation.
Classification and Presentation : Once data are collected , researcher has to arrange them in a format from which they would be able to draw some conclusions. The arrangement of data in groups according to some similarities is known as classification.
Tabulation is the process of presenting the classified data in the form of table. A tabular presentation of data becomes more intelligible and fit for further statistical analysis. Classified and Tabulated data can be presented in diagrams and graphs to facilitate the understanding of various trends as well as the process of comparison of various situations.
Analysis of Data : It is the most important step in any statistical enquiry . Statistical analysis is carried out to process the observed data and transform it in such a manner as to make it suitable for decision making.
Interpretation of Data : After analysing the data, researcher gets information partly or wholly about the population. Explanation of such information is more useful in real life. The quality of interpretation depends more and more on the experience and insight of the researcher.
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.
3. To provide techniques for making comparison: The primary purpose ot 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 1987, the per-capital income in India has increased by 10% in 1988. On the basis of this information, we shall be inla position to throw some light on the standard of living of an Indian in 1988.
4. 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.
5. 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.
6. To forecast future values: Some of the statistical techniques are used for forecasting future values of a variable. On 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.
7. 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.
8. 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.
9. 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.
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