For a regression model of executive compensation, you are given:

• Executive Compensation
  Coefficients:	Estimate	Std. Error	-statistic	-value
  (INTERCEPT)	–28,595.5	220.5	–129.7	<0.001
  AGEMINUS35	7,366.3	12.5	588.1	<0.001
  TOPSCHOOL	50.0	119.7	0.4	0.676
  LARGECITY	147.9	119.7	1.2	0.217
  MBA	2,490.9	119.7	20.8	<0.001
  YEARSEXP	15,286.6	7.2	2132.8	<0.001

• The acceptable significance level is [math]α = 0.10.[/math]

Determine which variable or variables should be removed first prior to rerunning the model.

• (INTERCEPT)
• AGEMINUS35, MBA, and YEARSEXP
• TOPSCHOOL
• TOPSCHOOL and LARGECITY
• YEARSEXP

Determine which of the following statements about prediction is true.

• Each of several candidate regression models must produce the same prediction.
• When making predictions, it is assumed that the new observation follows the same model as the one used in the sample.
• A point prediction is more reliable than an interval prediction.
• A wider prediction interval is more informative than a narrower prediction interval.
• A prediction interval should not contain the single point prediction.

A linear model has been fit to a dataset containing six predictor variables, F, G, H, I, J, and K. Determine which of the following statements regarding using Akaike information criterion (AIC) or Bayesian information criterion (BIC) to select an optimal set of predictor variables for this linear model is/are true.

• AIC and BIC provide a direct estimate of the test error.
• When choosing between the subsets {F, G, H} and {I, J, K}, AIC and BIC will always select the same subset.
• For large sample sizes (n > 7), the number of variables selected by BIC will be less than or equal to the number selected by AIC.

• None
• I and II only
• I and III only
• II and III only
• The correct answer is not given by (A), (B), (C), or (D).

In a simple linear regression model based on over 100 observations, you are given the following estimates.

1. The estimated slope is –1.03.
2. The standard error of the estimated slope is 0.06.

Calculate the 95% confidence interval for the slope.

• (–1.15, –0.91)
• (–1.13, –0.93)
• (–1.11, –0.95)
• (–1.09, –0.97)
• (–1.07, –0.99)

Toby observes the following coffee prices in his company cafeteria:

• 12 ounces for 1.00
• 16 ounces for 1.20
• 20 ounces for 1.40

The cafeteria announces that they will begin to sell any amount of coffee for a price that is the value predicted by a simple linear regression using least squares of the current prices on size.

Toby and his co-worker Karen want to determine how much they would save each day, using the new pricing, if, instead of each buying a 24-ounce coffee, they bought a 48- ounce coffee and shared it.

Calculate the amount they would save.

• It would cost them 0.40 more.
• It would cost the same.
• They would save 0.40.
• They would save 0.80.
• They would save 1.20.

Trevor is modeling monthly incurred dental claims. Trevor has 48 monthly claims observations and three potential predictors:

• Number of weekdays in the month
• Number of weekend days in the month
• Average number of insured members during the month

Trevor obtained the following results from a linear regression:

Determine which of the following variables should be dropped, using a 5% significance level.

• Intercept
• Number of weekdays
• Number of weekend days
• Number of members.

• I only
• II only
• III only
• IV only
• None should be dropped from the model