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Linear regression is the most basic and commonly used predictive analysis. Regression estimates are used to describe data and to explain the relationship between one dependent variable and one or more independent variables.
When the dependent variable is dichotomous(which takes 2 discrete values), we need to use the classification method(logistic regression). If the dependent variable is continuous, then we need to use linear regression. The reason for this is, for a linear regression, the errors must be normally distributed. But if the dependent variable is discrete, then assumption is not satisfied.