Question

Exercise 1. For this exercise use the bdims data set from the openintro package. Type ?bdims to read about this data set in the help menu. Of interest are the variables hgt (height in centimeters), wgt (weight in kilograms), and sex (dummy variable with 1-male, 0-female). Since ggplotO requires that a categorical variable be coded as a factor type in R, run the following code: library (openintro) bdíms$sex2 <-factor (bdins$sex, levels-c (0,1), labels=c('F', 'M')) (a) Use ggplot2 to make a scatter plot with hgt on the x-axis, and wgt on the y-axis. Color the points according to the dummy variable sex2. Use geom_smooth) to add the loast squares lines for each genuder to the scatter plot (b) Use 1m) to fit a linear regression model with ugt as the response variable and hgt (c) Write down the regression equation for the model fit in part (b). The model describes (d) Use 1m to fit a linear regression model with wgt as the response variable and hgt, and sex as the predictors. Use summary to print the results. two parallel lines; what are the equations for these two lines? sex, and the interaction between hgt and sex as predictors. Use summary to print the results. Is the interaction term significant? e) Write out the regression equation for the model fit in part (d). The model describes two unrelated regression lines (with different slopes and intercepts); what are the equ tions for these two lines?

Answer 1

Please find below required r code

#--------installing and getting in to global environment
install.packages("openintro")
library(openintro)
names(bdims)
#---Creating Factor
bdims$sex2<-factor(bdims$sex,levels = c(0,1),labels = c('F','M'))
# ------------ ggplot
ggplot(bdims,aes(bdims$hgt,bdims$wgt,colour=bdims$sex2)) +
geom_point()+geom_smooth(method="lm")
#----------model1
model<-lm(bdims$wgt~bdims$sex+bdims$hgt)
summary(model)
# regression equation is(wgt = -56.94 + 8.36 sex + 0.71hgt)
#-----------model 2
mode2<-lm(bdims$wgt~bdims$sex+bdims$hgt+(bdims$sex*bdims$hgt))
summary(mode2)
# regression equation is(wgt = -43.81 - 17.13 sex + 0.63hgt+0.14 (sex*hgt))

120 100 bdims$sex2 80- 60- 40- 160 170 180 190 200 150 bdims$hgt