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The general manager of the Cleveland Indians baseball team is in the process of

ID: 3050669 • Letter: T

Question

The general manager of the Cleveland Indians baseball team is in the process of determining which minor-league players to bring into the team so that later they would play as major-league players in his team. He is aware that his team needs players with high numbers of home-run (HR) hits and would like to find a way to predict the number of home runs a player will hit in major leagues. He gathers a random sample of players and records the number of home runs each player hit in his first two full years as a major-league player, the number of home runs he hits in his last full year in the minor leagues, his age, and the number of years of professional baseball.

Major HR Minor HR Age Years Pro

19 13 19 3

23 15 21 3

6 4 22 5

6 12 21 3

7 21 19 2

18 19 21 3

3 0 19 2

7 8 20 1

20 20 21 3

9 12 22 4

11 16 23 6

7 10 21 5

25 19 22 3

4 11 19 3

35 19 20 3

13 12 18 1

18 11 21 3

6 14 21 2

8 10 19 2

12 1 19 2

20 18 24 5

4 22 18 1

11 13 18 2

32 20 23 5

2 4 19 2

22 16 20 4

2 2 19 2

2 2 21 2

9 9 20 2

32 19 19 2

3 6 19 1

10 9 23 6

5 6 21 4

24 18 20 2

10 12 21 3

10 11 22 3

19 12 21 3

2 1 23 4

16 10 21 3

11 26 19 4

28 15 23 3

20 13 24 7

18 12 24 4

9 14 21 3

0 5 18 0

10 12 22 2

20 29 19 2

11 10 20 2

12 10 22 3

8 19 20 4

12 9 23 5

21 13 21 4

11 11 21 2

28 24 21 3

4 7 20 2

38 22 19 2

8 7 23 5

7 8 21 4

4 6 18 1

15 11 23 6

12 12 18 1

3 3 19 3

8 12 18 1

3 0 21 2

24 22 22 4

23 14 23 5

17 12 18 1

22 17 23 4

23 12 24 6

12 11 23 5

6 8 19 2

34 23 20 2

5 15 20 4

21 13 22 3

13 24 21 2

4 5 24 3

8 17 23 4

20 11 21 4

17 10 20 4

11 19 23 4

23 25 23 3

7 28 23 3

5 2 23 3

25 12 24 4

12 25 20 2

6 7 20 1

21 17 22 5

28 26 23 2

7 5 23 5

21 11 19 3

5 13 20 3

22 21 20 2

7 6 21 3

3 6 21 3

7 8 22 4

13 14 18 2

15 12 24 7

26 20 20 2

18 10 24 4

4 7 19 1

19 14 22 4

16 33 22 3

12 21 21 2

10 14 18 1

23 12 20 4

6 9 23 3

16 15 19 2

10 24 22 3

3 0 22 4

2 7 19 2

17 12 24 6

6 11 19 2

19 12 19 3

6 5 24 4

10 9 20 2

6 18 21 3

3 2 20 2

11 11 20 2

18 10 19 1

4 6 21 2

6 12 21 3

29 31 21 2

12 16 18 2

7 22 20 2

8 35 20 1

30 23 23 3

PART 1: Use the data in sheet “data for part 1”

Question 1

Looking at the range of values the variable number of home run hits in minor leagues can take,this variable is a ?

Select one:

a. Quantitative variable

b. Categorical variable

Question 2

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2-In this problem,number of hits in minor leagues is a …?

Select one:

a. predictor variable

b. response variable

c. none of the above

Question 3

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3-Which of the following equations properly explains the dependence of major home run hits on minor home run hits,age,and experience?

Select one:

a. Major HR = Minor HR + age + experience

b. Major HR = -0.206 + 7.640 Minor HR + 0.259 age + 1.754 experience

c. Major HR = -1.970 Minor HR + 0.666 age + 0.136 experience

d. Major HR = -1.970 + 0.666 Minor HR + 0.136 age + 1.176 experience

e. Major HR = 3.306 + 0.486 Minor HR + 0.320 age -1.073 experience

Question 4

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4-If the multiplier of age were 6.1 in the above model,it would best mean?

Select one:

a. If a player is one year older,he can hit 6.1 more major home runs on average.

b. For any given player,if one year passes with no baseball activity,he can hit 6.1 more major home runs.

c. If one year passes for a typical player with no baseball activity,he can hit 6.1 more major home runs on average.

d. If one year passes for a typical player who has been involved in professional baseball within the year,he can hit 6.1 more major home runs on average.

Question 5

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5-How much of the variation in data is explained by the above model?

Select one:

a. 35%

b. 59%

c. 5964

d. 6.99

Question 6

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6-How many major home runs a 25 year old novice with absolutely no professional experience in baseball or leagues is expected to have?

Select one:

a. -1.79

b. 1.42

c. 3.39

d. 0.14

Question 7

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7-Which of the following residual plots significantly violates the regression assumption that residuals should show no significant pattern?

Select one:

a. Plot of residuals versus minor home-runs

b. Plot of residuals versus experience

c. Both

d. None

Question 8

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8-Now create another regression model that would explain the dependence of major home run hits on only minor home run hits and experience (this is a model similar to question 3,with the difference that variable age is now excluded).What would be the equation of the regression line?

Select one:

a. Major HR = Minor HR + experience

b. Major HR = 4.485 + 0.658 Minor HR

c. Major HR = 3.306 + 0.486 Minor HR + 0.320 age -1.073 experience

d. Major HR = -1.970 + 0.666 Minor HR + 1.176 experience

e. Major HR = 0.453 + 0.668 Minor HR + 1.305 experience

Question 9

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9-Why is the adjusted R-squared in question 8 (with two predictors) more than that in question 3 (with three predictors)?

Select one:

a. Because the model with two predictors has a higher R-squared compared to the model with three predictors

b. Because the variable age was not explaining enough variability in the model with three predictors

c. This is the result of miscalculation by Excel regression

d. Because the variable age in the model with three predictors is much more influential than the other variables in explaining the response variable

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Going back to the model you developed in Question 3, we would like to investigate whether the developed model represents a good-fitting linear model. Assume a 5% significance level whenever needed.

Question 10

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10- Which of the following can represent the ALTERNATE hypothesis (H1H1) for testing the overall linear fit of the model you developed in mini-project 1 (as described above)?

Select one:

a. 123123

b. 1=2=3=01=2=3=0

c. 1010

d. At least two of the -values are different

e. At least one -value is not zero

Question 11

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11- What is the test statistic for testing the overall linear (the test outlined in question 10)?

Select one:

a. 1.86×10111.86×1011

b. 22

c. 0.35

d. 7.64

e. -0.21

Question 12

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12- Which of the following conclusions can be made when testing for the overall linear fit (the test of question 10)?

Select one:

a. All predictor variables have a significant impact on the number of major home runs

b. Number of major home runs has a significant impact on at least one of the predictor variables

c. At least one of the predictor variables have a significant impact on the number of major home runs

d. None of the predictor variables have a significant impact on the number of major home runs

Question 13

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13- Which of the following predictor variables does NOT have a significant impact on the number of major home runs?

Select one:

a. Number of minor home runs

b. Years of professional experience

c. Both

d. None

Question 14

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14- Which of the following pairs of predictor variables are highly correlated?

Select one:

a. Number of minor home runs & age

b. Number of minor home runs & years of experience

c. Age & years of experience

d. None

Question 15

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15- Which of the following variables cannot be removed without significantly hurting the model?

Select one:

a. Number of minor home runs

b. Age

c. Years of professional experience

d. Each one of the above can be removed

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PART 2: Use the data in sheet “data for part 2”

Major HR Minor HR Age Years Pro Type of hitter

19 13 19 3 power hitter

23 15 21 3 contact hitter

6 4 22 5 contact hitter

6 12 21 3 contact hitter

7 21 19 2 contact hitter

18 19 21 3 contact hitter

3 0 19 2 contact hitter

7 8 20 1 contact hitter

20 20 21 3 power hitter

9 12 22 4 contact hitter

11 16 23 6 power hitter

7 10 21 5 power hitter

25 19 22 3 power hitter

4 11 19 3 contact hitter

35 19 20 3 power hitter

13 12 18 1 power hitter

18 11 21 3 power hitter

6 14 21 2 contact hitter

8 10 19 2 power hitter

12 1 19 2 power hitter

20 18 24 5 power hitter

4 22 18 1 contact hitter

11 13 18 2 power hitter

32 20 23 5 power hitter

2 4 19 2 contact hitter

22 16 20 4 power hitter

2 2 19 2 contact hitter

2 2 21 2 contact hitter

9 9 20 2 power hitter

32 19 19 2 power hitter

3 6 19 1 contact hitter

10 9 23 6 contact hitter

5 6 21 4 contact hitter

24 18 20 2 power hitter

10 12 21 3 contact hitter

10 11 22 3 contact hitter

19 12 21 3 contact hitter

2 1 23 4 contact hitter

16 10 21 3 contact hitter

11 26 19 4 contact hitter

28 15 23 3 power hitter

20 13 24 7 contact hitter

18 12 24 4 power hitter

9 14 21 3 contact hitter

0 5 18 0 contact hitter

10 12 22 2 contact hitter

20 29 19 2 contact hitter

11 10 20 2 power hitter

12 10 22 3 contact hitter

8 19 20 4 power hitter

12 9 23 5 contact hitter

21 13 21 4 power hitter

11 11 21 2 power hitter

28 24 21 3 power hitter

4 7 20 2 power hitter

38 22 19 2 power hitter

8 7 23 5 power hitter

7 8 21 4 contact hitter

4 6 18 1 power hitter

15 11 23 6 contact hitter

12 12 18 1 power hitter

3 3 19 3 contact hitter

8 12 18 1 contact hitter

3 0 21 2 contact hitter

24 22 22 4 power hitter

23 14 23 5 power hitter

17 12 18 1 power hitter

22 17 23 4 power hitter

23 12 24 6 contact hitter

12 11 23 5 contact hitter

6 8 19 2 contact hitter

34 23 20 2 power hitter

5 15 20 4 power hitter

21 13 22 3 power hitter

13 24 21 2 power hitter

4 5 24 3 power hitter

8 17 23 4 contact hitter

20 11 21 4 contact hitter

17 10 20 4 contact hitter

11 19 23 4 contact hitter

23 25 23 3 power hitter

7 28 23 3 power hitter

5 2 23 3 contact hitter

25 12 24 4 contact hitter

12 25 20 2 contact hitter

6 7 20 1 power hitter

21 17 22 5 contact hitter

28 26 23 2 power hitter

7 5 23 5 contact hitter

21 11 19 3 contact hitter

5 13 20 3 power hitter

22 21 20 2 contact hitter

7 6 21 3 contact hitter

3 6 21 3 contact hitter

7 8 22 4 contact hitter

13 14 18 2 power hitter

15 12 24 7 contact hitter

26 20 20 2 power hitter

18 10 24 4 contact hitter

4 7 19 1 contact hitter

19 14 22 4 power hitter

16 33 22 3 power hitter

12 21 21 2 contact hitter

10 14 18 1 power hitter

23 12 20 4 power hitter

6 9 23 3 contact hitter

16 15 19 2 contact hitter

10 24 22 3 contact hitter

3 0 22 4 power hitter

2 7 19 2 contact hitter

17 12 24 6 power hitter

6 11 19 2 power hitter

19 12 19 3 power hitter

6 5 24 4 contact hitter

10 9 20 2 contact hitter

6 18 21 3 power hitter

3 2 20 2 contact hitter

11 11 20 2 power hitter

18 10 19 1 contact hitter

4 6 21 2 contact hitter

6 12 21 3 contact hitter

29 31 21 2 power hitter

12 16 18 2 contact hitter

7 22 20 2 contact hitter

8 35 20 1 power hitter

30 23 23 3 power hitter

In addition to the data set that was available before, the general manager has now acquired more information on the type of the baseball player when hitting the ball. Each player is classified to be either a “power hitter” or a “contact hitter”. Power hitters tend to exert more power when hitting the ball and therefore tend to strike out more often than contact hitters. The full data set is available in the second spreadsheet of the data file.

Question 16

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16 - Create a pivot table to display how does the type of hitter and years of experience influence the number of major home runs. What is the average number of major home runs for power hitters that have 2 or less years of experience (0, 1 or 2 years of experience)? (hint: “grouping” would be helpful)

Select one:

a. 10

b. 17.78

c. 13.89

d. 15.6

e. 13.15

Question 17

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17- Including the new variable for type of the hitter inside the regression model, which of the following is true when comparing power hitters with contact hitters,when other predictor variables are held constant?

Select one:

a. The difference in major home run hits between the two types of hitters is not significant

b. Power hitters have 3.58 MORE major home run hits than contact hitters on average

c. Power hitters have 3.58 LESS major home run hits than contact hitters on average

d. Power hitters have 4.5 MORE major home run hits than contact hitters on average

e. Power hitters have 4.5 LESS major home run hits than contact hitters on average

Explanation / Answer

1. Home runs is a quantitative variable

2.It is a predictor variable

3.Major HR = -1.970 + 0.666 Minor HR + 0.136 age + 1.176 experience

4.If a player is one year older,he can hit 6.1 more major home runs on average

5.. 59%

6.d. 0.14

7.Both the. Plot of residuals versus minor home-runs and Plot of residuals versus experience

8.Major HR = 0.453 + 0.668 Minor HR + 1.305 experience

9.Because the variable age was not explaining enough variability in the model with three predictors

10.e. At least one -value is not zero

12.c. At least one of the predictor variables have a significant impact on the number of major home runs

13.d. None

14.c. Age & years of experience

15.a. Number of minor home runs

16.c. 13.89

17.b. Power hitters have 3.58 MORE major home run hits than contact hitters on average

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