39.The National Basketball Association (NBA) would like to develop a multiple re
ID: 1214318 • Letter: 3
Question
39.The National Basketball Association (NBA) would like to develop a multiple regression model that would predict the number of wins for a team during the season. The following independent variables were considered for the model: field goal percentage (X1), free throw percentage (X2), turnovers per game (X3), rebounds per game (X4), and steals per game (X5). The following regression model was chosen using a data set of team statistics:
y = -276.8949 + 6.0284x1 - 6.8230x3 + 3.348x4
The first team from the data set had the following values: Wins = 56
Field goal percentage = 48.6%
Free throw percentage = 77.0% Turnovers per game = 14.6 Rebounds per game = 38.8 Steals per game = 8.2
The residual for this team is .
A) 9.6 B) -3.1 C) 7.0 D) -5.2
TRUE/FALSE. Write 'T' if the statement is true and 'F' if the statement is false.
40.One of the assumptions for the multiple regression model is that the residuals have a constant variance.
ESSAY. Write your answer in the space provided or on a separate sheet of paper.
Use the information below to answer the following question(s).
The table below shows the number of interceptions thrown during the season by seven randomly selected National Football League teams and the number of games those teams won during the season.
Wins
Interceptions
3
28
6
19
11
16
14
6
10
9
8
25
8
11
41.Use the NFL team data to calculate the total sum of squares, sum of squares error, and sum of squares regression.
MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
42.The following distribution shows the frequency distribution of the number of shots a particular NBA player blocked in one game for a random sample of 100 games.
Blocked Shots per Game
Frequency
0
0
1
14
2
35
3
36
4
10
5
2
6
3
You have been assigned the task to test if the distribution of blocked shots per game for this player follows the Poisson distribution using = 0.05. The sample mean for this distribution is .
A) 3.47 B) 2.60 C) 3.12 D) 2.20
Wins
Interceptions
3
28
6
19
11
16
14
6
10
9
8
25
8
11
Explanation / Answer
1) Residual is the difference between the predicted value and the actual or measured value. Here the measured number of wins is 56. Predicted number of wins is:
y = -276.8949 + 6.0284(48.6) - 6.8230(14.6) + 3.348(38.8)
= 46.37
So the residual is 52 - 46.37 or 5.6
So the answer is D.
2) One of the assumptions for the multiple regression model is that the residuals have a constant variance. This statement is true.
3) The table provides the data analysis of the NFL data. The residual SS and Regression SS together make up the total SS.
df SS MS F Significance F Regression 1 17.08221 17.08221 3.047974 0.15577 Residual 4 22.41779 5.604447 Total 5 39.5Related Questions
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