a) Use software to find the multiple linear regression equation. Enter the coefficients rounded to 4 decimal places. b) Use the multiple linear regression equation to predict the salary for a baseball player with an RBI of 41 and HR of 25. Round your answer to 1 decimal place, do not convert numbers to dollars. millions of dollars c) Holding all other variables constant, what is the correct interpretation of the coefficient b1 = 0.111 in the multiple linear regression equation? %3D O For each HR, a baseball player's predicted sallary increases by 0.111 million dollars. OFor each RBI, a baseball player's predicted sallary increases by 0.111 million dollars. O f the baseball player's salary increases by 0.111 million dollars, then the predicted RBI will increase by one. O If the baseball player's salary increases by 0.111 million dollars, then the predicted RBI will increase by 0.0371. d) Holding all other variables constant, what is the correct interpretation of the coefficient b = 0.0371 in the multiple linear regression equation? O If the baseball player's salary increases by 0.0371 million dollars, then the predicted HR will increase by one. O For each HR, a baseball player's predicted sallary increases by 0.0371 million dollars. O If the baseball player's salary increases by 0.0371 million dollars, then the predicted HR will increase by 0.111. O For each RBI, a baseball player's predicted sallary increases by 0.0371 million dollars.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
We wish to predict the salary for baseball players (y) using the variables RBI (x1) and HR (x2), then we use a regression equation of the form yˆ=b0+b1x1+b2x2
- HR - Home runs - hits on which the batter successfully touched all four bases, without the contribution of a fielding error.
- RBI - Run batted in - number of runners who scored due to a batters's action, except when batter grounded into double play or reached on an error
- Salary is in millions of dollars.
![The following is a chart of baseball players' salaries and statistics from 2016.
Player Name
Miquel Cabrera
Yoenis Cespedes
Ryan Howard
Albert Pujols
Robinson Cano
Mark Teixeira
Joe Mauer
RBI's HR's
Salary (in millions)
28.050
27.500
108
38
86
31
59
119
25
25.000
25.000
31
103
39
24.050
23.125
44
15
49
111
11
23.000
22.750
22.125
21.857
21.667
21.571
Hanley Ramirez
Justin Upton
30
87
90
31
Adrian Gonzalez
18
Jason Heyward
Jayson Werth
Matt Kemp
Jacoby Ellsbury
Chris Davis
Buster Posey
49
7
70
108
21
35
21.500
21.143
56
84
38
14
21.119
20.802
80
17
Shin-Soo Choo
7
20.000
20.000
20.000
Troy Tulowitzki
Ryan Braun
Joey Votto
Hunter Pence
Prince Fielder
79
91
97
57
44
24
31
29
20.000
18.500
18.000
18.000
13
Adrian Beltre
104
86
32
Victor Martinez
27
25
18.000
17.454
17.000
17.000
16.083
Carlos Gonzalez
100
Matt Holliday
Brian McCann
Mike Trout
David Ortiz
62
20
20
58
100
127
83
29
38
Adam Jones
Curtis Granderson
Colby Rasmus
Matt Wieters
J.D. Martinez
Brandon Crawford
16.000
16.000
16.000
15.800
15.800
29
30
59
54
15
17
66
68
22
6.750
84
48
12
6.000
5.950
12.000
11.000
10.500
Rajai Davis
Aaron Hill
12
38
55
76
90
53
24
10
Сосо Crisp
Ben Zobrist
Justin Turner
Denard Span
13
18
27
5.100
5.000
4.550
11
Chris lannetta
7
Leonys Martin
Justin Smoak
Jorge Soler
Evan Gattis
47
15
4.150
3.900
34
14
31
12
3.667
3.300
72
32
Logan Forsythe
Jean Segura
52
64
20
2.750
2.600
20](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb9849c3b-f0ff-47eb-829a-2c91d3fc6b02%2F1550c71f-a667-41fe-8e8c-5193976a254f%2Fam318w_processed.png&w=3840&q=75)
![a) Use software to find the multiple linear regression equation. Enter the coefficients rounded to 4 decimal
places.
b) Use the multiple linear regression equation to predict the salary for a baseball player with an RBI of 41
and HR of 25. Round your answer to 1 decimal place, do not convert numbers to dollars.
millions of dollars
c) Holding all other variables constant, what is the correct interpretation of the coefficient bị
the multiple linear regression equation?
0.111 in
O For each HR, a baseball player's predicted sallary increases by 0.111 million dollars.
O For each RBI, a baseball player's predicted sallary increases by 0.111 million dollars.
O lf the baseball player's salary increases by 0.111 million dollars, then the predicted RBI will increase
by one.
Olf the baseball player's salary increases by 0.111 million dollars, then the predicted RBI will increase
by 0.0371.
d) Holding all other variables constant, what is the correct interpretation of the coefficient b2 = 0.0371
in the multiple linear regression equation?
Olf the baseball player's salary increases by 0.0371 million dollars, then the predicted HR will increase
by one.
O For each HR, a baseball player's predicted sallary increases by 0.0371 million dollars.
Olf the baseball player's salary increases by 0.0371 million dollars, then the predicted HR will increase
by 0.111.
O For each RBI, a baseball player's predicted sallary increases by 0.0371 million dollars.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb9849c3b-f0ff-47eb-829a-2c91d3fc6b02%2F1550c71f-a667-41fe-8e8c-5193976a254f%2F0zia1fe_processed.png&w=3840&q=75)
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