Using the data is ps5q1.dta, well examine the relationship between child height and parental education.

reg female meduc meducfem deduc deducfem Source SS df MS = Model Residual 253.284287 36.9551622 4 1,156 63.3210716 .031968133 Number of obs F(4, 1156) Prob > F R-squared Adj R-squared Root MSE II| IIII| III 1,161 1980.76 0.0000 0.8727 0.8722 . 1788 = Total 290.239449 1,160 250206421 = female Coefficient Std. err. t P>|t| (95% conf. intervall meduc meducfem deduc deducfem -cons -.0297645 .0531218 -.0209141 .0417671 .5356685 0024158 .0033114 .0023114 .0032511 0146684 -12.32 16.04 -9.05 12.85 36.52 0.000 0.000 0.000 0.000 0.000 -.0345044 .0466248 -.0254492 0353884 .5068888 -.0250247 .0596188 - .016379 0481458 .5644482 Question 1 Using the data is ps5q1.dta, we'll examine the relationship between child height and parental education. The data contains information on height, age, gender identify (only male and female were given as options), and parental years of education for a random sample of 1,161 Indonesian children. Note that child height is a great marker of nutrition and early life health. a) Begin by estimating and reporting the results from the following equation: height; = Qo + aimeduci + a2deduci + Wi (1) 1 Where meduc are years of education of child i's mother, and deduc are years of education of child i's father. b) Is there a statistically significant relationship between maternal education and height at the 5% significance level? Is there a statistically significant relationship between paternal education and height at the 5% significance level? State how you know in each case. c) What is the SSR from this model? Suppose we wanted to look at regression results by gender identity. d) Reestimate and provide results for equation (1) separately for students that identify as boys and girls (you will do 2 different regressions where you use the reg command with an "if" statement). 1 reg female meduc meducfem deduc deducfem Source SS df MS = Model Residual 253.284287 36.9551622 4 1,156 63.3210716 .031968133 Number of obs F(4, 1156) Prob > F R-squared Adj R-squared Root MSE II| IIII| III 1,161 1980.76 0.0000 0.8727 0.8722 . 1788 = Total 290.239449 1,160 250206421 = female Coefficient Std. err. t P>|t| (95% conf. intervall meduc meducfem deduc deducfem -cons -.0297645 .0531218 -.0209141 .0417671 .5356685 0024158 .0033114 .0023114 .0032511 0146684 -12.32 16.04 -9.05 12.85 36.52 0.000 0.000 0.000 0.000 0.000 -.0345044 .0466248 -.0254492 0353884 .5068888 -.0250247 .0596188 - .016379 0481458 .5644482 Question 1 Using the data is ps5q1.dta, we'll examine the relationship between child height and parental education. The data contains information on height, age, gender identify (only male and female were given as options), and parental years of education for a random sample of 1,161 Indonesian children. Note that child height is a great marker of nutrition and early life health. a) Begin by estimating and reporting the results from the following equation: height; = Qo + aimeduci + a2deduci + Wi (1) 1 Where meduc are years of education of child i's mother, and deduc are years of education of child i's father. b) Is there a statistically significant relationship between maternal education and height at the 5% significance level? Is there a statistically significant relationship between paternal education and height at the 5% significance level? State how you know in each case. c) What is the SSR from this model? Suppose we wanted to look at regression results by gender identity. d) Reestimate and provide results for equation (1) separately for students that identify as boys and girls (you will do 2 different regressions where you use the reg command with an "if" statement). 1