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. (a) Interpret the estimated intercept.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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Chapter4: Equations Of Linear Functions
Section4.6: Regression And Median-fit Lines
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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.
(a) Interpret the estimated intercept.
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. (a) Interpret the estimated intercept.
Description of variables: Weight is birth weight in grams, Boy is equal
to 1 if the baby is a boy, 0 if it is a girl, Married is 1 if the mother is married,
0 if unmarried.
Education of the mother is divided into four categories: less than high
school, high school (dummy variable Ed_Hs), some college (dummy variable
Ed_SmCol), and college graduate (dummy variable Ed_Col). The omitted
category is "less than high school," so coefficients must be interpreted rela-
tive to this category.
Smoke is equal to 1 if the mother smokes, 0 if she does not, Cigs Per is
cigarettes smoked per day, Black is 1 if the mother is black, 0 otherwise.
Mom Age is age in years, M_WtGain is mother's weight gain in pounds.
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: 165535
Included observations: 65535
Huber-White-Hinkley (HC1) heteroskedasticity consistent standard errors
and covariance
Variable
BOY
MARRIED
ED_COL
ED_HS
ED_SMCOL
SMOKE
CIGSPER
BLACK
MOM_AGE_CNTRD
Coefficient Std. Error
3316.786 8.106849
104.6528 4.231952
66.44096 5.699306
27.51704 7.816031
8.680020 6.494597
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
Prob(Wald F-statistic)
5.641921
MOM AGE_CNTRD^2 -0.514637
M_WTGAIN_CNTRD 9.618949
M_WTGAIN_CNTRD^2 -0.027913
t-Statistic
409.1338
24.72921
11.65773
3.520590 0.0004
1.336498
0.1814
3.386994
0.0007
0.0000
24.48548 7.229266
-200.6533 11.36470 -17.65585
-1.260510 0.812260
-1.551855
-200.5243 6.468994 -30.99775
12.21205
Prob.
0.0000
0.0000
0.0000
0.113853 Mean dependent var
0.113691 S.D. dependent var
541.4975 Akaike info criterion
1.92E+10 Schwarz criterion
-505483.1
701.5267
0.000000 Wald F-statistic
0.000000
0.461996
0.064432 -7.987346 0.0000
0.198337 48.49802
0.008685 -3.214042
Hannan-Quinn criter.
Durbin-Watson stat
0.1207
0.0000
0.0000
0.0000
0.0013
3347.636
575.1800
15.42675
15.42856
15.42731
1.957147
623.6461
Transcribed Image Text:Description of variables: Weight is birth weight in grams, Boy is equal to 1 if the baby is a boy, 0 if it is a girl, Married is 1 if the mother is married, 0 if unmarried. Education of the mother is divided into four categories: less than high school, high school (dummy variable Ed_Hs), some college (dummy variable Ed_SmCol), and college graduate (dummy variable Ed_Col). The omitted category is "less than high school," so coefficients must be interpreted rela- tive to this category. Smoke is equal to 1 if the mother smokes, 0 if she does not, Cigs Per is cigarettes smoked per day, Black is 1 if the mother is black, 0 otherwise. Mom Age is age in years, M_WtGain is mother's weight gain in pounds. 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: 165535 Included observations: 65535 Huber-White-Hinkley (HC1) heteroskedasticity consistent standard errors and covariance Variable BOY MARRIED ED_COL ED_HS ED_SMCOL SMOKE CIGSPER BLACK MOM_AGE_CNTRD Coefficient Std. Error 3316.786 8.106849 104.6528 4.231952 66.44096 5.699306 27.51704 7.816031 8.680020 6.494597 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) Prob(Wald F-statistic) 5.641921 MOM AGE_CNTRD^2 -0.514637 M_WTGAIN_CNTRD 9.618949 M_WTGAIN_CNTRD^2 -0.027913 t-Statistic 409.1338 24.72921 11.65773 3.520590 0.0004 1.336498 0.1814 3.386994 0.0007 0.0000 24.48548 7.229266 -200.6533 11.36470 -17.65585 -1.260510 0.812260 -1.551855 -200.5243 6.468994 -30.99775 12.21205 Prob. 0.0000 0.0000 0.0000 0.113853 Mean dependent var 0.113691 S.D. dependent var 541.4975 Akaike info criterion 1.92E+10 Schwarz criterion -505483.1 701.5267 0.000000 Wald F-statistic 0.000000 0.461996 0.064432 -7.987346 0.0000 0.198337 48.49802 0.008685 -3.214042 Hannan-Quinn criter. Durbin-Watson stat 0.1207 0.0000 0.0000 0.0000 0.0013 3347.636 575.1800 15.42675 15.42856 15.42731 1.957147 623.6461
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