Statistics and its Importance and limitations

Statistics

Statistics means quantitative information or quantifications of the facts and findings. There must be a system, method or technique to collect quantitative information.

Statistical information may be in raw form then it needed to be classified, tabulated, or to be systematically presented.

Also, there must be a set of methods and techniques to condense the data and analysis and interpretation of quantitative information. The study of all these methods and techniques is statistics.

In view of such a vastness of subject matter, it has come to be defined both in singular sense and plural sense.

Statistics- A Plural Noun

In plural sense, it refers to information in terms of numbers or numerical data, such as population data, employment data, concerning public expenditure, etc.

However, every numerical data is not statistics.

For example, Aman gets Rs 200 per month as pocket allowance is not statistics as it is neither aggregate nor average, whereas average pocket allowance of the class 10 is Rs 220 is statistics.

So, we can say that all statistics are data but all data are not statistics.

It is numerical statements of facts in any department of enquiry placed in relation to each other.” —- BOWLEY

By this we mean quantitative data affected to a marked extent by multiplicity of causes.”——- YULE AND KENDALL

FEATURES OF STATISTICS IN PLURAL SENSE

Main features of statistics in plural sense are:-

  • Aggregate of Facts:

 A single number does not constitute statistics. No conclusion can be drawn from it. It is only aggregate number of facts that can be called statistics, as they can be compared and comparison can be drawn from them.

Therefore, all statistics can be expressed in numbers but all numbers are not statistics.

  • Numerically Expressed:

Statistics are expressed in terms of numbers. Qualitative aspects like small, big, rich, poor, etc. are not statistics.

  • Affected by multiplicity of causes:

It is not affected by single factor, but are influenced by many factors. If they will be affected by only one factor then by removing that factor they will lose all their significance.

  • Reasonable accuracy:

A reasonable degree of accuracy must be kept in view while collecting statistical data. This accuracy depends on the purpose of investigation, its nature, size, and available resources.

  • Placed in Relation to each other:

Numerical alone will be called statistics as they are mutually related and so comparable. Unless they have the quality of comparison they cannot be called as statistics.

  • Pre-determined Purpose:

It is collected with some pre-determined objective. Any information collected without any definite purpose will only be a numerical value and not statistics.

  • Enumerated or estimated:

It may be collected by enumeration or the same be estimated. If the field of investigation is vast, the procedure of estimation may be helpful.

  • Collected in a Systematic Manner:

It should be collected in a systematic manner. Before preparing them a plan must be prepared. No conclusion can be drawn from it collected in haphazard manner.

STATISTICS – A SINGULAR NOUN

In the singular sense, it means science of statistics or statistical methods.

It refers to the techniques or methods relating to collection, classification, presentation, analysis, and interpretation of quantitative data.

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

Lovitt, “Statistics is the science which deals with the collection, classification and tabulation of numerical facts as the basis for the explanation, description and comparison of phenomena”.

Seligman,“Statistics is the science which deals with the collection, classifying, presenting, comparing and interpreting numerical data collected to throw some light on any sphere of enquiry”.

Importance of Statistics

Its main importance in different fields is discussed below:

In economics: We all know that the study of economy or economics depends on different variables, based on the economic data of a specie economy.

This is just another way of saying that economics is completely based on the study of economic statistics.

Economic statistics are used for calculating various factors such as GDP (Gross Domestic Product) and GNP (Gross National product), which are essential for knowing our exact economic condition.

It also alert us about any trend developing, which can be utilized for developing sound economic strategies.

In natural and social sciences: For any of the natural sciences, experimentation is very important.

Now, for the precise measurement of results, their tabulation, i.e. recording and comparison is required, which is nothing but a form of statistics.

Similarly, in social sciences scenario, it is very important to consider all the data related to the subjects in observation.

Since social science spectrums include a great number of subjects, mass data collection and assimilation is inevitable

This can be a really tedious task if not done using proper statistical channels.

In planning: In order to make planning realistic in any economy, the objectives are set in quantitative terms.

It help in visualizing the target quantitatively and evaluating the achievements.

This, in turn, helps in our decision making in every eld which includes other Nance decisions as well.

In Information Technology (IT): As information technology also deals with organization and interpretation of numerical facts. In fact, most of the principles of information technology are based on concepts of statistics which is required in almost every eld in which there is a requirement of interpretation on numeral facts.

Statistics and business: Business forecasting, pricing, investment decisions, production controls etc. for the business are possible only by means of the statistic. Thus, it acts as the best facilitator in the modern business age.

Statistics and pure science: It is also a helpful tool in science like biology, astronomy, and medical science.

Francis Galton used, “regression analysis in biological science”. In astronomy, the Theory of Gauss is developed by using the least square method of statistics for the study of the movement of stars and planets.

In banking sector: The banking sector is very important for the general public. This sector, too, uses statistical data utilization approach for each functioning.

The banking sector works on the money exchange system. They collect money from depositors and give money to people who want to borrow. All the while banks earn interest, a part of which they offer to the depositors.

Limitations:

 Like other discipline, it is also not free from its limitations. Some major limitations are discussed below:

It does not deal with an individual:

Particular numerical facts, individual data are not related to statistics. We do not use a singular form of data as a datum, but we always consider it. In this sense, we can also say that it does not deal with an individual. For example, a student’s marks in economics cannot be considered as statistics; but the marks obtained by all the students make statistics.

It is not suitable for the study of qualitative phenomenon:

A qualitative phenomenon like honesty, culture, love, hatred, etc which cannot be expressed numerically is not capable of direct statistical analysis. However, we can express this phenomenon indirectly in terms of numbers and analysed in it.

Statistical relations are not exact:

Most of the statistical analyses are based on the collected date that may not be 100% correct. If the data are not correct, then the results obtained from such data cannot be expected to be 100% accurate. Thus, it just describes the phenomena on the average.

It is liable to be misused:

Experts can analyse and use this in the study. There is a great possibility of its misuse, any person can misuse it. If misused by untrained, unskilled or dishonest person, it will give harmful results.

It is only a means:

It acts as a facilitator or a supporting subject to the other disciplines. It helps to analyse data and draw a conclusion from the endings. Thus, it is only a means.      

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