Question

Suppose the following table was generated from the sample data of 2020 teachers relating annual salary to months of teaching experience and gender.

Coefficients | Standard Error | t Stat | P-Value | |
---|---|---|---|---|

Intercept | 39456.64693339456.646933 | 244.443412244.443412 | 161.414237161.414237 | 0.0000000.000000 |

Months of Experience | 61.40231861.402318 | 8.6513608.651360 | 7.0974187.097418 | 0.0000020.000002 |

Female (1 if female, 0 if male) | 874.703963874.703963 | 250.099136250.099136 | 3.4974293.497429 | 0.0027590.002759 |

Step 1 of 2: In this regression equation, what is the intercept value for men? Enter your answer in the space provided. Do not round your answer.

Step 2 of 2: In this regression equation, what is the intercept value for women? Enter your answer in the space provided. Do not round your answer.

Answer #1

we have given

Coefficients | Standard Error | t Stat | P-Value | |
---|---|---|---|---|

Intercept | 39456.646933 | 244.443412 | 161.414237 | 0.000000 |

Months of Experience | 61.402318 | 8.651360 | 7.097418 | 0.000002 |

Female (1 if female, 0 if male) | 874.703963 | 250.099136 | 3.497429 | 0.002759 |

the regression equation is

y = 39456.646933 +61.402318 Months of Experience +874.703963 Female (1 if female, 0 if male)

Step 1 of 2: In this regression equation, the intercept value for men is

39456.646933 |

Step 2 of 2: In this regression equation, what is the intercept value for women is 39456.646933 + 874.703963 = 40331.35

Suppose the following table was generated from the sample data
of 20 campuses relating the total number of crimes committed to the
number of police officers on campus and if the college or
university is private.
Coefficients
Standard Error
t-stat
P-Value
Intercept
559.505805
19.468953
28.738361
0.000000
# of officers
-6.845383
0.631437
-10.840960
0.000000
Private (1 if private, 0 otherwise)
-55.712802
8.049521
-6.921257
0.000002
Step 1 of 2: In this regression equation, what is the intercept
value for colleges or universities...

Suppose the following table was generated from the sample data
of 20 20 campuses relating the total number of crimes committed to
the number of police officers on campus and if the college or
university is public. Coefficients Standard Error t Stat P-Value
Intercept 565.130664 565.130664 18.192314 18.192314 31.064254
31.064254 0.000000 0.000000 Number of Officers −7.434598 −7.434598
0.565905 0.565905 −13.137537 −13.137537 0.000000 0.000000 Public (1
if public, 0 otherwise) −42.284220 −42.284220 6.212333 6.212333
−6.806496 −6.806496 0.000003 0.000003
Step 1 of...

Suppose the following table was generated from the sample data
of 20 employees relating annual salary to years of education and
gender. According to the results, is there a salary difference
between men and women at the 0.05 level of significance? If yes,
write the difference in salary in the space provided, rounded to
two decimal places. Else, select "There is not enough
evidence."
Coefficients
Standard Error
t Stat
P-Value
Intercept
−15910.435186
1986.259992
−8.010248
0.000000
Education
4129.465091
114.058730
36.204726
0.000000...

Suppose the following table was generated from the sample data
of 20 employees relating annual salary to years of education and
gender. According to the results, is there a salary difference
between men and women at the 0.05 level of significance? If yes,
write the difference in salary in the space provided, rounded to
two decimal places. Else, select "There is not enough
evidence."
Coefficients
Standard Error
t Stat
P-Value
Intercept
?24331.924717
3419.740424
?7.115138
0.000002
Education
4578.868673
214.295364
21.367092
0.000000...

Suppose the following regression equation was generated from
sample data relating annual salary to experience, gender, and
marital status. Gender is represented by a dummy variable, FEMALEi
where FEMALEi=1 if employee i is female and FEMALEi=0 if employee i
is male. Marital status is represented by a dummy variable MARRIEDi
where MARRIEDi=1 if employee i is married and MARRIEDi=0 if
employee i is single.
SALARYi=45399.358869+522.095299EXPERIENCEi−2445.498353FEMALEi−42.875876EXPERIENCEi⋅FEMALEi+10156.223595MARRIEDi−98.638952EXPERIENCEi⋅MARRIEDi−14314.347804FEMALEi⋅MARRIEDi+ei
1)According to the regression equation above, what is the
estimated change in salary resulting from...

Suppose the following regression equation was generated from
sample data relating annual salary to experience, gender, and
marital status. Gender is represented by a dummy variable,
FEMALEiFEMALEi, where FEMALEi=1FEMALEi=1 if employee i is female
and FEMALEi=0FEMALEi=0 if employee i is male. Marital status is
represented by a dummy variable MARRIEDiMARRIEDi where
MARRIEDi=1MARRIEDi=1 if employee i is married and
MARRIEDi=0MARRIEDi=0 if employee i is single.
SALARYi=46905.309796+429.685020EXPERIENCEi−2445.945436FEMALEi−35.464377EXPERIENCEi⋅FEMALEi+10084.736168MARRIEDi−60.572088EXPERIENCEi⋅MARRIEDi−14238.984644FEMALEi⋅MARRIEDi+eiSALARYi=46905.309796+429.685020EXPERIENCEi−2445.945436FEMALEi−35.464377EXPERIENCEi⋅FEMALEiSALARYi=+10084.736168MARRIEDi−60.572088EXPERIENCEi⋅MARRIEDi−14238.984644FEMALEi⋅MARRIEDi+ei
According to the regression equation above, what is the
estimated starting salary for married women?...

Suppose the following regression equation was generated from
sample data relating salary to years of experience, marital status,
and the interaction term of years of experience and marital status.
Marital status is a dummy variable where MARRIEDi=1MARRIEDi=1 if
employee i is married and MARRIEDi=0MARRIEDi=0 if employee i is
single.
SALARYi=58316.795901+790.675473EXPERIENCEi+1222.075701MARRIEDi−36.766201EXPERIENCEiMARRIEDi+ei
1) In this regression equation, what is the intercept value for
married employees?
2)In this regression equation, what is the value of the slope
for married employees?

Suppose the following table was generated from sample data of
2020 employees relating hourly wage to years of experience and
whether or not they have a college degree. Using statistical
software, create an indicator (dummy) variable for the variable
"Degree" and find the regression equation. Is there enough evidence
to support the claim that on average employees with a college
degree have higher hourly wages than those without a college degree
at the 0.050.05 level of significance? If yes, write...

The following table was generated from the sample data of 10
college students regarding the number of parking tickets the
student receives in a semester, the student's age, and the
student's GPA. The dependent variable is the student's GPA, the
first independent variable (x1) is the number of parking tickets,
and the second independent variable (x2) is the student's age.
Coefficients Standard Error t-Stat p-value Intercept −8.593245
1.831876 −4.690952 0.005381 Number of Parking Tickets −0.023715
0.045205 −0.524623 0.622265 Student's Age...

Consider the following computer output of a multiple regression
analysis relating annual salary to years of education and years of
work experience.
Regression Statistics
Multiple R
0.7345
R Square
0.5395
Adjusted R Square
0.5195
Standard Error
2134.9715
Observations
49
ANOVA
df
SS
MS
F
Significance F
Regression
2
245,644,973.9500
122,822,486.9750
26.9460
1.8E-08
Residual
46
209,672,760.0092
4,558,103.4785
Total
48
455,317,733.9592
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
14271.51879
2,525.5672
5.6508
0.000000963
9187.8157
19,355.2219
Education (Years)
2351.3035...

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