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It is one of the most widely known modeling technique. Linear regression is usually among the first few topics which people pick while learning predictive modeling. In this technique, the dependent variable is continuous, independent variable(s) can be continuous or discrete, and nature of regression line is linear.
In regression there are typically two types of F values. One is an omnibus F, which if high suggests that overall the linear model is better than just taking a straight average as the prediction, and individual F values for each predictor, which if high suggest that adding the predictor to the model helps predict the response.