धन की मात्रा सिद्धांत - फिशर का

Statistics

अर्थशास्त्र

Statistics

 The statistical interpretation of numerical details is called Statistics. 

Statistics can be defined in two ways.



In the meaning of singular, statistics are from statistical methods, such as compilation of data, organization, classification, analysis and interpretation.
Statistical in the meaning of plural, statistics mean the systematic stored numerical facts.

Area of statistics

Use of statistics in ancient times only by the kings to administer their own administration

But the importance of statistics has increased in today’s era and all those

In areas where numerical facts are used, it has spread like

Economics, industry, commerce, physics, chemistry etc. Human economic activities

There is no such area where statistics are not used.

 

Importance of Statistics in Economics

  1. It makes the economist able to present financial facts in a precise form.
  2. Help reduce the number of figures in the form of some numerical measurements
  3. Use of Statistics to find out the relation between various economic factors.
  4. Economists are able to predict financially through numerical studies.
  5. Statistics are helpful in the creation of economic policies, which help in economic problems may be the solution.
  1. Helps in reviewing the results of prior economic policies.



Work of statistics

  1. Statistics simplifies complexity.
  2. Statistics reveals facts as numbers.
  3. Statistics summarize summo form.
  4. Statistics compile and relate them in various syncretes.
  5. Statistics is helpful in determining policy.
  6. Statistics are helpful in economic forecast.

Statistical limitations

  1. Statistics do not study individual units.
  2. Statistical conclusions can cause confusion.
  3. Statistical rules are only true on average.
  4. Statistics only studies numerical facts.
  5. Use of statistics is only possible by experts.
  6. Synthesis of symmetry and homogeneity is required.
  7. Misuse of statistics is the biggest limit. Because the wrong thing can also prove to be correct by statistics.



2 comments

Comments are closed.