The term “regression“literally mean “stepping back towards the average”. It was first used by a British biometrician Sir Francis Galton, in connection with the inheritance of stature. Galton found that the offspring’s of abnormally tall or short parents tend to “regress” or “step back” to the average population height. But the term “regression” as now used in statistics is only a convenient term without having any reference to biometry.

Regression analysis is a mathematical measure of the average relationship between two or more variables in terms of the original units of the data.

In regression analysis there are two types of variables. The variables whose value is influenced or is to be predicted is called dependent variable and the variable which influences the values or is used for prediction, is called independent variable. In regression analysis independent variable is also known as regressor or predictor or explanatory variable while the dependent variable is also known as regressed or explained variable.

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- Bivariate Normal Distribution
- Multiple And Partial Correlation
- Plane Of regression
- Properties If residuals
- Coefficient Of Multiple Correlation
- Properties of Multiple Correlation coefficient
- Coefficient Of Partial Correlation
- Multiple correlation In terms Of Total And Partial Correlation
- Coefficient In Terms Of Regression
- Expression For Partial Correlation

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