Question 81) A healthcare executive is using regression to p

81) A healthcare executive is using regression to predict total revenues. She has decided to include both patient length of stay and insurance type in her model. Insurance type can be grouped into three categories: Government-Funded, Private-Pay, and Other. Her model is

A) Y = b0.

B) Y = b0 + b1X1.

C) Y = b0 + b1 X1 + b2X2.

D) Y = b0 + b1 X1 + b2 X2 + b3X3.

E) Y = b0 + b1 X1 + b2 X2 + b3X3 + b4X4.

82) 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 r2was .83, with an adjusted r2of .82 and her level of significance was .003. In the second model, she included both patient length of stay and insurance type. The r2was .84 and the adjusted r2was .80 for the second model and the level of significance did not change. Which of the following statements is true?

A) The second model is a better model.

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 r2always increases when additional variables are added to the model.

E) None of the above statements are true.

83) The sum of the squares total (SST)

A) measures the total variability in Y about the mean.

B) measures the total variability in X about the mean.

C) measures the variability in Y about the regression line.

D) measures the variability in Xabout the regression line.

E) indicates how much of the total variability in Y is explained by the regression model.

84) Which of the following statements provides the best guidance for model building?

A) If the value of r2increases as more variables are added to the model, the variables should remain in the model, regardless of the magnitude of increase.

B) If the value of the adjusted r2increases as more variables are added to the model, the variables should remain in the model.

C) If the value of r2increases as more variables are added to the model, the variables should not remain in the model, regardless of the magnitude of the increase.

D) If the value of the adjusted r2increases as more variables are added to the model, the variables should not remain in the model.

E) None of the statements provide accurate guidance.

85) Which of the following is not a common pitfall of regression?

A) If the assumptions are not met, the statistical tests may not be valid.

B) Nonlinear relationships cannot be incorporated.

C) Two variables may be highly correlated to one another but one is not causing the other to change.

D) Concluding that a statistically significant relationship implies practical value.

E) Using a regression equation beyond the range of X is very questionable.

86) The condition of an independent variable being correlated to one or more other independent variables is referred to as

A) multicollinearity.

B) statistical significance.

C) linearity.

D) nonlinearity.

E) The significance level for the F-test is not valid.

87) The primary difference between r2 and the adjusted r2is that

A) the adjusted r2 accounts for the total number of variables in the regression model.

B) the adjusted r2 accounts for the number of independent variables in the regression model.

C) the adjusted r2 accounts for the number of dependent variables in the regression model.

D) the adjusted r2 accounts for multicollinearity.

E) None of the above

88) Which of the following is true regarding a regression model with multicollinearity, a high r2value, and a low F-test significance level?

A) The model is not a good prediction model.

B) The high value of r2is due to the multicollinearity.

C) The interpretation of the coefficients is valuable.

D) The significance level tests for the coefficients are not valid.

E) The significance level for the F-test is not valid.

89) An automated process to systematically add or delete independent variables from a regression model is called

A) nonlinear regression.

B) linear regression.

C) residual analysis.

D) stepwise regression.

E) sensitivity analysis.

90) When an independent variable is correlated with one other independent variable, the variables are said to be

A) collinear.

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