Use the following data to develop a curvilinear model to predict y. Include both x1 and x2 in the model in addition to x21 and x22, and the interaction term x1x2. Comment on the overall strength of the model and the significance of each predictor. Develop a regression model with the same independent variables as the first model but without the interaction variable. Compare this model to the model withinteraction.
Answer to relevant QuestionsWhat follows is Excel output from a regression model to predict y using x1, x2, x21, x22, and the interaction term, x1x2. Comment on the overall strength of the model and the significance of each predictor. The data follow ...Use a stepwise regression procedure and the following data to develop a multiple regression model to predict y. Discuss the variables that enter at each step, commenting on their t values and on the value ofR2.In Problem 14.17, you were asked to use stepwise regression to predict premiums earned by net income, dividends, and underwriting gain or loss. Study the stepwise results, including the regression coefficients, to determine ...Use the x1 values and the log of the x1values given here to predict the y values by using a stepwise regression procedure. Discuss the output. Was either or both of the predictorssignificant?Shown below is output from two Excel regression analyses on the same problem. The first output was done on a “full” model. In the second output, the variable with the smallest absolute t value has been removed, and the ...
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