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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. (b) Are boys, on average, heavier than girls at birth, all other factors being equal? If so, by how much? Is the difference between boys and girls estimated from this regression statistically significant at the 5% level?

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. (b) Are boys, on average, heavier than girls at birth, all other factors being equal? If so, by how much? Is the difference between boys and girls estimated from this regression statistically significant at the 5% level?

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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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. (b) Are boys, on average, heavier than girls at birth, all other factors being equal? If so, by how much? Is the difference between boys and girls estimated from this regression statistically significant at the 5% level?
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. (b) Are boys, on average, heavier than girls at birth, all other factors being equal? If so, by how much? Is the difference between boys and girls estimated from this regression statistically significant at the 5% level?
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, O 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, CigsPer 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 ponds. 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 66.44096 27.51704 8.680020 24.48548 -200.6533 -1.260510 -200.5243 5.641921 MOM AGE_CNTRD^2 -0.514637 9.618949 M_WTGAIN_CNTRD^2 -0.027913 8.106849 4.231952 5.699306 7.816031 6.494597 7.229266 11.36470 0.812260 6.468994 409.1338 24.72921 11.65773 3.520590 1.336498 3.386994 -17.65585 -1.551855 -30.99775 12.21205 0.0000 0.0000 0.0000 0.0004 0.1814 0.0007 0.0000 0.1207 0.0000 0.0000 BOY MARRIED ED_COL ED_HS ED SMCOL SMOKE CIGSPER BLACK MOM_AGE_CNTRD 0.461996 0.064432 0.198337 -7.987346 48.49802 0.0000 0.0000 0.0013 M_WTGAIN CNTRD 0.008685 -3.214042 R-squared Adjusted R-squared S.É. of regression Sum squared resid Log likelihood F-statistic 0.113853 Mean dependent var 0.113691 541.4975 Akaike info criterion 1.92E+10 Schwarz criterion -505483.1 3347.636 575.1800 15.42675 15.42856 15.42731 1.957147 623.6461 S.D. dependent var Hannan-Quinn criter. Prob(F-statistic) Prob(Wald F-statistic) 701.5267 Durbin-Watson stat 0.000000 0.000000 Wald F-statistic
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, O 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, CigsPer 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 ponds. 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 66.44096 27.51704 8.680020 24.48548 -200.6533 -1.260510 -200.5243 5.641921 MOM AGE_CNTRD^2 -0.514637 9.618949 M_WTGAIN_CNTRD^2 -0.027913 8.106849 4.231952 5.699306 7.816031 6.494597 7.229266 11.36470 0.812260 6.468994 409.1338 24.72921 11.65773 3.520590 1.336498 3.386994 -17.65585 -1.551855 -30.99775 12.21205 0.0000 0.0000 0.0000 0.0004 0.1814 0.0007 0.0000 0.1207 0.0000 0.0000 BOY MARRIED ED_COL ED_HS ED SMCOL SMOKE CIGSPER BLACK MOM_AGE_CNTRD 0.461996 0.064432 0.198337 -7.987346 48.49802 0.0000 0.0000 0.0013 M_WTGAIN CNTRD 0.008685 -3.214042 R-squared Adjusted R-squared S.É. of regression Sum squared resid Log likelihood F-statistic 0.113853 Mean dependent var 0.113691 541.4975 Akaike info criterion 1.92E+10 Schwarz criterion -505483.1 3347.636 575.1800 15.42675 15.42856 15.42731 1.957147 623.6461 S.D. dependent var Hannan-Quinn criter. Prob(F-statistic) Prob(Wald F-statistic) 701.5267 Durbin-Watson stat 0.000000 0.000000 Wald F-statistic
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