Question

1. A sample of 33 companies was randomly selected and data collected on the average annual

bonus ($), turnover rate (%), and trust index (measured on a scale of 0 — 100). The regression

equation is TurnoverRate = 12.1005 -0.07149TrustIndex -0.0007216AverageBonus. The correct

interpretation for the coefficient of Averager Bonus is

A) After accounting for Trust Index, an increase of $10,000 in annual bonus is associated with a

decrease of 7.216% in turnover rate.

B) After accounting for Trust Index, an increase of $100 in annual bonus is associated with a

decrease of 7.216% in turnover rate, on average.

C) None of these.

D) After accounting for Trust Index, an increase of $10,000 in annual bonus is associated with a

decrease of 7.216% in turnover rate, on average.

E) After accounting for Trust Index, increasing the annual bonus by $100 will decrease the

turnover rate by 7.216%.

2. Data are collected on the number of tourists to a city (thousand) and total tourism revenue

($million) for a sample of 20 cities in US. According to the following output, what is the 99%

confidence interval of regression slope for this regression model?

A) (0.224, 0.357)

B) (0.158, 0.489)

C) (0.173, 0.526)

D) (0.089, 0.634)

E) (0.108, 0.542)

3. To determine what affects turnover rate, a sample of 33 companies was randomly selected and data were collected on the average annual bonus and turnover rate (%). In addition, a questionnaire was administered to the employees of each company to arrive at a trust index (measured on a scale of 0–100). Below are the multiple regression results. In addition, they made two plots to check the assumptions for the multiple regression.

According to the two plots above, which of the following statement(s) is(are) correct?

I.Equal Variance and Linearity assumptions are NOT satisfied

II. Equal Variance and Linearity Assumptions are satisfied.

III. Independence Assumption is satisfied.

IV. Normality Assumption is satisfied.

V. Independence Assumption is NOT satisfied.

A) I and IV.

B) I and III.

C) II and IV.

D) II and III.

E) I and V.

Regression Analysis: Tourism Revenue ($million) versus Tourists (thousand) The regression equation is: Tourism ($million) = 15.747 + 0.32479 Tourists (thousand) Predictor Coef SE Coef 15.747 2.455 Constant Tourists (thousand) 0.32479 0.07547 S 1.7386 63.4% R-Sq Dependent Variable is Turnover Rate Predictor Coef SE Coef T 12.1005 0.7826 15.46 0.000 Constant Trust Index -0.07149 0.01966 3.64 0.001 Average Bonus -0.0007216 0.0001481 -4.87 0.000 s = 1.49746 R-Sq 79.6% R-Sq (adj) 78.3% Versus Fits (respanse is Turnower Rate) 2 10 Rted Value Residual 12 Histogram (respanse is Turnover Rate) 14 12 10 Residual Frequency

Answer 1

Answer 1) After accounting for Trust Index, an increase of $10,000 in anmual bonus is associated with a decrease of 7.216% in turnover rate, on average Option D is correct.

2)

The 99% confidence interval of regression slope for tourists is, First, compute thef critical value then find confidence interval The t critical value is, The sample size is small and two-tailed test. Look in the column headed a 0.01 and the row headed in the t distribution table by using degree of freedom is, = d.f.=n-2 = 20-2 = 18 The t critical value is 2.878 Parameter estimate ±txStandard error of parameter estimate 99% C.I. 0.325 2.878 x 0.075 0.325 0.216 =0.109 to 0.541 The 99% confidence interval of regression slope for tourists is 0.109 to 0.541

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