Evaluate the predictive appropriateness of the linear model (the linear regression equation). Support your evaluation with analysis values including the coefficient of determination.That is my question given to me above, I just do not understand how to evaluate the predictive appropriateness from the linear regression equation. Can you please help me?

Question
Asked Oct 13, 2019

Evaluate the predictive appropriateness of the linear model (the linear regression equation). Support your evaluation with analysis values including the coefficient of determination.

That is my question given to me above, I just do not understand how to evaluate the predictive appropriateness from the linear regression equation. Can you please help me?

check_circleExpert Solution
Step 1

Solution: We have to evaluate the predictive appropriateness of the linear model.

Step 2

The predictive appropriateness of the linear model is described by various factors:

Coefficient of Determination

The standard error of the estimate

Significance of the model

Step 3

The coefficient of determination or R-square tells us the amount of variation in the dependent variable that is explained by the independent variable. The coefficient of variation lies between 0 and 1. The closer the value of coefficient of determination to 1, the more appropriate is the model. For example if the coefficient of determination is 0.80, it means 80% of variation in the dependent variable is explained by the independent variable.

The standard error of estimate is the average deviation o...

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