Page 135 - DECO504_STATISTICAL_METHODS_IN_ECONOMICS_ENGLISH

Unit 9: Correlation: Definition, Types and its Application for Economists

(4) Croxton and Lowden define correlation as, “When the relationship of a quantitative nature, the Notes
appropriate statistical tool for discovering and measuring the relationship and expressing it in
a brief formula is known as correlation.”
(5) As per Prof. Boddington, “Whenever some definite connection exists between two or more groups,
classes or series of data, there is said to be correlation.”
From the above definitions it can be said that correlation is a statistical tool which requires about the
relationship between two or more variables.
Utility: Correlation has immense utility in various fields of knowledge. Some of the important areas
where correlation has been used successfully are:
(1) In the field of genetics: Galton and Pearson developed a method of assessing correlation which
was used in studying many problems of biology and genetics.
(2) In the field of management: Basically, management is all about making decisions. Correlation
technique presents a strong tool into the hands of the manager which reduces the range of
uncertainity associated with decision-making. Moreover, it also helps in identifying the
stabilishing factors for a disturbed economic situation.
(3) Other field of social sciences: Correlation helps in determining the interrelationships between
different variables and in this way it is very helpful in promoting research and opening new
frontiers of knowledge.
In this way it can be said that correlation has immense utility in various fields in promoting
research and opening new frontiers of knowledge.

Correlation is very useful in understanding the economic behaviour. It helps in
locating those variables on which other variables depend. In this way various
economic events can be analysed.

“Correlation” and “cause and effect relationship”

Correlation measures a degree of the relationship between two or more variables but it does not
indicate any kind of cause and effect relationship between the variables. If, high degree of correlation
is found exist between two variables, it implies that there must be a reason for such close relationship,
but the cause and effect relation can be revealed specifically when other knowledge of the factor
involved being brought to bear on the situation. This means, to establish a ‘functional relationship’
between two or more variables, one has to go beyond the confines of statistical analysis to other
factors. (Functional relationship means that two or more factors are interdependent. In fact, although,
high degree of correlation may mean that two or more variables are mutually dependent, but at the
same time, this high degree of correlation may be due to many other reasons like:
(1) The two variables are being affected by a third variable or by more than one variable.
(2) The two variables might be mutually affecting each other and neither of them is the cause or the
effect.
(3) The high degree of correlation between two variables comes out just by chance or by sheer coincidence.
Therefore, although high degree of correlation does not necessarily indicate the cause and effect
relationship. The quantitative tool requires the support of proper knowledge and logic about the variables
on the basis of which the results should be interpreted. In this way, although ‘correlation’ in a strong
tool it needs to be used carefully by those who have knowledge otherwise its misuse is quite likely.
Types of Correlation

Correlation can be classified as given ahead:
(1) Positive and negative correlation: When the values of the two variables move in the same
direction, i.e., an increase in one is associated with an increase in other, or vice versa, the correlation

LOVELY PROFESSIONAL UNIVERSITY 129