Regression to predict total revenues


A healthcare executive is using regression to predict total revenues. She is deciding whether or not to include both patient length of stay and insurance type in her model. Her first regression model only included patient length of stay. The resulting r2 was .83, with an adjusted r2 of .82 and her level of significance was .003. In the second model, she included both patient length of stay and insurance type. The r2 was .84 and the adjusted r2 was .80 for the second model and the level of significance did not change. Which of the following statements is true?

a. None of the above statements are true.

b. The first model is a better model.

c. The r2 increased when additional variables were added because these variables significantly contribute to the prediction of total revenues.

d. The adjusted r2 always increases when additional variables are added to the model.

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Basic Statistics: Regression to predict total revenues
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