O An F test O Extrapolation is used to test the hypothesis that the values of the regression parameters Bo, B₁, B2, ... Bq are all zero. O The least squares method O Attest
The f-test basically compares your model to one with zero predictor variables (the intercept alone model) and determines if your extra coefficients improved the model. If you get a specific outcome, it means that the coefficients you put in your model enhanced its fit.
A regression model is frequently used for extrapolation, or anticipating the reaction to an input that goes outside the range of the predictor variable values used to fit the model.
The Least Squares Regression Line is the line that minimizes the vertical distance between the data points and the regression line. The term "least squares" refers to the optimum line of fit that minimizes variation (the sum of squares of the errors).
A t-test is a hypothesis-testing tool used in linear regression to examine the linearity of the connection between both the response variable and several predictor factors.
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