Suppose a null model is applied to describe the relation of two random variables, you may add one more variable into the model as a predictor, and that would be the second model.
a. Draw two scatter plots to illustrate the fitting of the two models, which can show simple regression has a better fitting.
b. Tell how the R^2 changes and how adjusted R^2 change.
c. Write an estimator of the coefficient of the null model.
a. Draw two scatter plots to illustrate the fitting of the two models, which can show simple regression has a better fitting.
Ans:
in the scatter plot, first shows the more grouping than the second one
b. Tell how the R^2 changes and how adjusted R^2 change.
if we add the extra independent variable then R2 is always increses with extra addition of the variables.
in such a situation we have to look in to the adjested R2 value .
if both R and Adj R2 both are increasing then the added extra variable has significant contribution in the model.
c. Write an estimator of the coefficient of the null model.
the coefficent in the regression model are intercept and regression coefficeint
b = SP/SSX where SP -Sum of products (SP) and SSX sum of square of X
a= MY - bMX
Thanks
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