Are boys, on average, heavier than girls at birth, all other factors being equal? If so, by how much? Is the di§erence between boys and girls estimated from this regression statistically significant at the 5% level?
Are boys, on average, heavier than girls at birth, all other factors being equal? If so, by how much? Is the di§erence between boys and girls estimated from this regression statistically significant at the 5% level?
Trigonometry (MindTap Course List)
8th Edition
ISBN:9781305652224
Author:Charles P. McKeague, Mark D. Turner
Publisher:Charles P. McKeague, Mark D. Turner
Chapter4: Graphing And Inverse Functions
Section: Chapter Questions
Problem 6GP: If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use...
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Are boys, on average, heavier than girls at birth, all other factors being
equal? If so, by how much? Is the di§erence between boys and girls
estimated from this regression statistically significant at the 5% level?
Transcribed Image Text:The last two variables are entered into the regression as centered around their
mean, Mom_Age_Cntrd and M_WtGain_Cntrd, i.e. Mom_Age_Cntrd
is the variable Mom_Age minus the average age of Mom_Age, and simi-
larly for M_WtGain_Cntrd. The average age of mothers is 27.2 years and
the average weight gain is 30.8 pounds.
Dependent Variable: WEIGHT
Method: Least Squares
Date: 03/11/22 Time: 15:19
Sample: 1 65535
Included observations: 65535
Huber-White-Hinkley (HC1) heteroskedasticity consistent standard errors
and covariance
Variable
Coefficient
Std. Error
t-Statistic
Prob.
3316.786
104.6528
8.106849
409.1338
0.0000
BOY
4.231952
24.72921
0.0000
MARRIED
66.44096
5.699306
11.65773
0.0000
ED_COL
ED_HS
ED_SMCOL
SMOKE
27.51704
7.816031
3.520590
0.0004
8.680020
6.494597
1.336498
0.1814
24.48548
-200.6533
-1.260510
-200.5243
7.229266
3.386994
0.0007
11.36470
-17.65585
0.0000
CIGSPER
0.812260
-1.551855
0.1207
BLACK
6.468994
-30.99775
0.0000
5.641921
0.461996
12.21205
0.0000
MOM_AGE_CNTRD
MOM_AGE_CNTRD^2 -0.514637
M_WTGAIN_CNTRD
M_WTGAIN_CNTRD^2 -0.027913
0.064432
-7.987346
0.0000
9.618949
0.198337
48.49802
0.0000
0.008685
-3.214042
0.0013
0.113853 Mean dependent var
0.113691 S.D. dependent var
541.4975 Akaike info criterion
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
Prob(Wald F-statistic)
3347.636
575.1800
15.42675
1.92E+10 Schwarz criterion
15.42856
-505483.1 Hannan-Quinn criter.
15.42731
701.5267 Durbin-Watson stat
1.957147
0.000000 Wald F-statistic
623.6461
0.000000
Transcribed Image Text:A dataset contains data on birth weights of 65535 babies born in June 1997
along with variables that are potentially related to birth weights. The sample
is restricted to singleton births, with mothers recorded as either black or
white, between the ages of 18 and 45, resident in the United States.
With the aim to investigate factors influencing the weight of babies at
birth, a regression of Weight on a range of variables has been carried out.
A description of variables is given below and the estimation results can be
found on the following page.
Referring to these results, answer the following questions. Keep in mind
that two of the regressors, Mom_Age and M_WtGain, are entered in the
regression in terms of the deviations from their mean.
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