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Unit 10: Correlation
In other words, one of the basic functions of a manager is to understand the relationship between Notes
these variables and make appropriate decisions keeping the future in mind known as ‘Forecasting
or Prediction’. The part which deals with understanding of the behaviour of variables is
Correlation and the part deal with the forecasting is Regression.
10.1 Correlation
Correlation is a statistical tool for studying the relationship between two or more variables and
correlation analysis involves various methods and techniques used for studying and measuring
the extent of relationship between the two variables. Two variables said to be correlated, if the
change in one variable results in a corresponding change in the other. Various experts have
defined correlation in their own words and their definitions, broadly speaking, imply that
correlation is the degree of association between two or more variables. Some important
definitions of correlation are given below:
1. “If two or more quantities vary in sympathy so that movements in one tend to be
accompanied by corresponding movements in other(s) then they are said to be correlated.”
— L.R. Connor
2. “Correlation is an analysis of covariation between two or more variables.”
— A.M. Tuttle
3. “When the relationship is of a quantitative nature, the appropriate statistical tool for
discovering and measuring the relationship and expressing it in a brief formula is known
as correlation.”
— Croxton and Cowden
4. “Correlation analysis attempts to determine the ‘degree of relationship’ between
variables“.
— Ya Lun Chou
Correlation Coefficient: It is a numerical measure of the degree of association between two or
more variables.
Did u know? What is the scope of correlation analysis?
The existence of correlation between two (or more) variables only implies that these
variables (i) either tend to increase or decrease together or (ii) an increase (or decrease) in
one is accompanied by the corresponding decrease (or increase) in the other. The questions
of the type, whether changes in a variable are due to changes in the other, i.e., whether a
cause and effect type relationship exists between them, are not answered by the study of
correlation analysis. If there is a correlation between two variables, it may be due to any
of the following situations:
1. One of the variable may be affecting the other: A correlation coefficient calculated
from the data on quantity demanded and corresponding price of tea would only
reveal that the degree of association between them is very high. It will not give us
any idea about whether price is affecting demand of tea or vice-versa. In order to
know this, we need to have some additional information apart from the study of
correlation. For example if, on the basis of some additional information, we say that
the price of tea affects its demand, then price will be the cause and quantity will be
the effect. The causal variable is also termed as independent variable while the other
variable is termed as dependent variable.
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