Pearson’s correlation coefficient is the method of measuring the correlation. It is known as the best method of measuring a correlation, because it is based on the method of covariance. It gives information about the magnitude of correlation as well as the direction of the relationship.
Assumptions:
- Independent of case: Cases should be independent to each other.
- Distribution: Variables of the correlation should be normally distributed.
- Linear relationship: Two variables should be linearly related to each other, or if we plot the value of variables on a scatter diagram, it should yield a relatively straight line.
Properties:
- Limit: Coefficient values lie between +1 to -1.
- Pure number: It is independent of the unit of measurement. For example, if one variable’s unit of measurement is in inches and the second variable is in quintals, even then, Pearson’s correlation coefficient value does not change.
- Symmetric: Correlation of the coefficient between two variables is symmetric . This means between X and Y or Y and X, the value of will remain the same.
Degree of correlation:
- Perfect: If the value is near ± 1, then it said to be a perfect correlation.
- High degree: If the value lies between ± 0.75 and ± 1, then it is said to be a high degree of correlation.
- Moderate degree: If the value lies between ± 0.25 and ± 0.75, then it is said to be moderate degree of correlation.
- Low degree: When the value lies between 0 and ± 0.25, then it is said to be a low degree of correlation.
- No correlation: When the value is zero.
Related Pages:
