Question
In: Economics
Given the following regression equation with dependent variable is NHL player salaries (with t-statistics in parentheses:...
Given the following regression equation with dependent variable is NHL player salaries (with t-statistics in parentheses:
Salary = 566,400 + 71,928 Goals + 20,403 Assists + 98,430 All-Star (3.45) (2.96) (3.5) (1.30)
R2 = 0.95
where: Salary= NHL Salary in $
Goals= Number of career goals
Assists = Number of career assists All-Star =1 if
All-Star in the previous season, 0 otherwise.
A. Interpret the R2.
B. Interpret the each of the coefficient—What do they mean (do they make sense?) Are they statistically significant? What is economic significance of each?
Solutions
Rahul Sunny answered 2 years agoRelated Solutions
The following are regression results where Car Price is the dependent variable: Regression Statistics ?2=0.446R2=0.446 Adjusted...
The following are regression results where Car Price is the
dependent variable:
Regression Statistics
?2=0.446R2=0.446 Adjusted ?2=0.441R2=0.441 Observations =
804
Independent Variables
Coefficients
Standard Error
t Stat
P-value
Intercept
6758.76
1876.967
3.601
0.000
Mileage
-0.17
0.032
-5.326
0.000
Cylinder
3792.38
683.180
5.551
0.000
Liter
-787.22
867.062
-0.908
0.364
Doors
-1542.75
320.456
-4.814
0.000
Cruise
6289.00
657.992
9.558
0.000
Sound
-1993.80
571.776
-3.487
0.001
Leather
3349.36
597.681
5.604
0.000
Car Price is measured in dollars. The independent variables
are:
Mileage: number...
a. If they are going to run a linear regression, identify which variable should be the independent variable and which should be the dependent variable in a regression equation.
In seeking to determine how influential advertising is, the management of a recently established retail chain collected data on sales revenue and advertising expenditure from its' stores over the last ten (10) weeks. The table below shows the data collected: Advertising Expenditure ($ 000) Sales ($ 000) 3 5 76 50 250 700 450 3.5 75 4 150 4.5 7 200 750 7.5 800 8.5 1,100
a. If they are going to run a linear regression, identify which variable should...
Consider the following regression equation for the United States (standard errors in parentheses): where: Pt ...
Consider the following regression equation for the United States
(standard errors in parentheses):
where: Pt = per capita
pounds of pork consumed in time period t
PRPt = the price of pork in time period t
PRBt = the price of beef in time period t
YDt = per capita disposable income in time
period t
(a) Hypothesize signs and specify the appropriate null and
alternative hypotheses for the coefficients of each of these
variables.
(b)...
The following is a chart of 25 baseball players' salaries and statistics from 2016. Player Name...
The following is a chart of 25 baseball players' salaries and
statistics from 2016.
Player Name
RBI's
HR's
AVG
Salary (in millions)
Joe Mauer
49
11
0.261
23.000
Robinson Cano
103
39
0.298
24.050
Leonys Martin
47
15
0.245
4.150
Brandon Crawford
84
12
0.275
6.000
Colby Rasmus
54
15
0.206
15.800
Carlos Gonzalez
100
25
0.298
17.454
Matt Kemp
108
35
0.268
21.500
Prince Fielder
44
8
0.212
18.000
Mark Teixeira
44
15
0.204
23.125
Yoenis Cespedes
86
31...
The following is a chart of 25 baseball players' salaries and statistics from 2019. Player Name...
The following is a chart of 25 baseball players' salaries and
statistics from 2019.
Player Name
RBI's
HR's
AVG
Salary (in millions)
Adam Jones
67
16
0.260
4.500
Marwin Gonzalez
55
15
0.264
12.000
Wil Myers
53
18
0.239
5.500
Christian Vazquez
72
23
0.276
2.850
Adam Eaton
49
15
0.279
8.400
Joey Votto
47
15
0.261
25.000
Stephen Piscotty
44
13
0.249
7.333
DJ LeMahieu
102
26
0.327
12.000
Max Kepler
90
36
0.252
6.000
Christian Yelich
97
44...
(1) Estimate a multiple regression equation with the price-earnings ratio (P/E) as the dependent variable and...
(1) Estimate a multiple regression equation
with the price-earnings ratio (P/E) as the dependent variable and
the following as independent variables: intercept, gross profit
margin, sales growth, dummy variable for industry 1, and dummy
variable for industry 2.
(2 ) Create a set of dummy variables for each
of the three industries.
(3) Interpret the regression results:
(a) adjusted R-square
(b) F-statistic
(c) t-statistics for each of the coefficients
(4) Calculate a P/E ratio point estimate for a
firm with...
1.) Use Excel to plot the dependent vs the independent variable. Show the regression equation from...
1.) Use Excel to plot the dependent vs the independent variable.
Show the regression equation from the computer output.
Lannie Karner- GPA 3.6 Income 75k
Courtney Sheperd Gpa 3.3 Income 74K
Zenobia Roussel- GPA 2.9 Income 66K
Elaine Doody- GPA 3.8 Income 80k
Maudie Hocker-GPA 3.1 Income 65k
Rick Hoover-GPA 3.2 Income 53k
Franinca Ortez-GPA 2.7 Income 65k
Li Kinder-GPA 3.3 Income 71k
Brad Clem-GPA 3.8 Income 80k
Soon Nettleton-GPA 4.0 Income 95k
Vertie Yousesef-GPA 3.9 Income 110k
Love Au-GPA...
Refer to this regression equation: (standard errors in parentheses.) Q = 8,400 - 10 P...
Refer to this regression equation:
(standard errors in parentheses.)
Q = 8,400 - 10 P + 5 A + 4 Px + 0.05 I
(1,732) (2.29) (1.36) (1.75) (0.15)
R2 = 0.65
N = 120
F = 35.25
Standard error of estimate = 34.3
Q = Quantity demanded
P = Price = 1,000
A = Advertising expenditures, in thousands = 40
PX = price of competitor's good = 800
I = average monthly income = 4,000
1) Calculate the...
Refer to this regression equation: (standard errors in parentheses.) Q = 8,400 - 10 P...
Refer to this regression equation:
(standard errors in parentheses.)
Q = 8,400 - 10 P + 5 A + 4 Px + 0.05 I
(1,732) (2.29) (1.36) (1.75) (0.15)
R2 = 0.65
N = 120
F = 35.25
Standard error of estimate = 34.3
Q = Quantity demanded
P = Price = 1,000
A = Advertising expenditures, in thousands = 40
PX = price of competitor's good = 800
I = average monthly income = 4,000
1) Calculate the...
The following output was obtained from a regression analysis of the dependent variable Rating and an...
The following output was obtained from a regression analysis of
the dependent variable Rating and an independent variable Price.
(10 points)
ANOVA
df
SS
MS
F
Regression
1
372.707
372.707
42.927
Residual
15
130.234
8.682
Total
16
502.941
Coefficients
Standard Error
t Stat
P-value
Intercept
45.623
3.630
12.569
0.000
Price
0.107
0.016
6.552
0.000
Use the critical value approach to perform an F test for the
significance of the linear relationship between Rating and Price at
the 0.05 level of...
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