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Methods of Studying Simple Correlation

A simple and attractive method of measuring correlation by diagrammatically representing bivariate distribution for determination of the nature of the correlation between the variables is known as Scatter Diagram Method. This method gives a visual idea to the investigator/analyst regarding the nature of the association between the two variables. It is the simplest method of studying the relationship between two variables as there is no need to calculate any numerical value. 

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According to Karl Pearson, “Coefficient of Correlation is calculated by dividing the sum of products of deviations from their respective means by their number of pairs and their standard deviations.”

This method of measuring the coefficient of correlation is the most popular and is widely used. It is denoted by ‘r’, where r is a pure number which means that r has no unit. 



N = Number of Pair of Observations

x = Deviation of X series from Mean (X-\bar{X})

y = Deviation of Y series from Mean (Y-\bar{Y})

\sigma_x  = Standard Deviation of X series (\sqrt{\frac{\sum{x^2}}{N}})

\sigma_y  = Standard Deviation of Y series (\sqrt{\frac{\sum{y^2}}{N}})

r = Coefficient of Correlation

Spearman’s Rank Correlation Coefficient is a method of calculating the correlation coefficient of qualitative variables . In other words, the formula determines the correlation coefficient of variables like beauty, ability, honesty, etc., whose quantitative measurement is not possible. Therefore, these attributes are ranked or put in the order of their preference.



rk = Coefficient of rank correlation

D = Rank differences

N = Number of variables

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