Paper 4: Fundamentals of Business Mathematics & Statistic

6.2 I FUNDAMENTALS OF BUSINESS MATHEMATICS AND STATISTICS

Correlation and Regression

6.1.2. Importance of Correlation

A car owner knows that there is a definite relationship between petrol consumed and distance travelled.

Thus on the basis of this relationship the car owner can predict the value of one on the basis of other.

Similarly if he finds that there is some distortions of relationship, he can set it right.

Correlation helps in the following ways

1. It helps to predict event and the events in which there is time gap i.e. it helps in planning


2. It helps in controlling events.
   6.1.3. Types of Correlation
   Correlation can be classified under the following heads-


3. Positive and negative correlation


4. Simple multiple and partial correlation


5. Linear and non-linear correlation

6.1.4. Positive and Negative Correlation

Two variables are said to be positively correlated when both the variables move in the same direction. The

correlation is said to be positive (directly related) when the increase in the value of one variable is

accompanied by an increase in the value of the other variable and vice versa.

Two variables are said to be negatively correlated when both the variables move in the opposite direction.

The correlation is said to be negative (inversely related) when the increase in the value of one variable is

accompanied by a decrease in the value of the other variable and vice versa.

6.1.5. Simple, Multiple and Partial Correlation

Correlation is said to be simple when only two variables are studied.

In multiple correlation three or more variables are studied simultaneously.

In partial correlation though more than two variables are recognised, but only two are considered to be

influencing each other; and the effect of other influencing variables are kept constant.

6.1.6. Linear and Non-linear Correlation

If the amount of change in one variable tends to bear a constant ratio to the amount of change in the

other variable, then the correlation is said to be linear.

The correlation is said to be non-linear if the amount of change in one variable does not bear a constant

ratio to the amount of change in the other related variable.