9.5.Introduction to Simple linear regression

Unit 9 - Correlation and regression

9.5 Introduction to Simple Linear Regression
If two variables are found to be highly correlated then a more useful approach would be to study the nature of their relationship. Regression analysis achieves this by formulating statistical models which can best describe these relationships. These models enable prediction of the value of one variable, called the dependent variable from the known values of the other variable(s). It differs from correlation in that regression estimates the nature of relationship where as the correlation coefficient estimates the degree or intensity of relationship. Further, it is necessary to designate one of the variables as dependent and the other as independent in the case of regression analysis which is not necessary in correlation analysis.
Simple linear regression deals with the study of near relationships involving two variables, whereas, the relationships among more than two variables are studied of multiple regression techniques.



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