Regression equations of Y on X and X on Y.Ģ. A computer while calculating correlation coefficient between two variables X and Y from 25 pairs of observations obtained the followingįind the correlation coefficient of X and Y. For example, in the correlation of heights of fathers and sons, a tendency of human race to return to or regress to the average height is observed.ġ. The meaning of regression is a tendency of returning to the mean. The functional relation between the variables is called as regression equation. We derive the equation that defines the relationship, which is linear, as we have defined linear correlation in the previous sections. If the relationship is established and is significant then next step is to obtain the expression of relationship of the variables. Coefficient of correlation gives the magnitude of the association of two variables. We know that such relationships are measured using coefficient of correlation. Such kind of analysis is required if the data we have is dependent on each other or have some type of causal relationship. We may be interested in knowing if the demand of a commodity has been in the past then what will be the future demand may be two years later if the same trend continues.
Like if price is increased how will demand be affected. In business many a times we want to predict what may happen if some action is taken.
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