1.-The dataset below contains (fictional) data on medical costs and their possib

1.-The dataset below contains (fictional) data on medical costs and their possible determinants. The variables in the dataset are
Age: age of the policy holder
Sex: sex of policy holder (male or female)
BMI: Body mass index of policy holder
Children: Number of dependents covered by health insurance policy
Tobacco: tobacco use status (yes or no)
Region: geographic region where policy holder is located (North, South, East or West)
Charges: medical costs billed to health insurance
You want to study the determinants of medical costs. Estimate the full model that includes all explanatory variables. Based on your results, which region has the highest baseline medical costs?
a.North
b.
South
c.
East
d.
West
2.
Conduct a suitable hypothesis test that the coefficients of all insignificant variables (at the 5% level) from the full model in the previous question are jointly 0. Please enter the result of your test statistic (rounded to two decimals) below.
(If your answer is less than 1, please also enter the zero before the decimal point. That is, if your answer is 1/2, please enter 0.50 instead of .50)
3. based on the hypothesis test in the previous question, we reject fail to reject should should not the null hypothesis that these coefficients are jointly 0. Therefore they reject fail to reject should should not be included in the model.
4.
In this question, we will consider an alternative model to estimate the determinants of medical costs.Using the medical cost data from the previous questions, create a dummy variable only for the North region. To do this in R, use the following line of code (you’ll need to replace name_of_your_dataframe by the actual name of your dataframe for this to work):
name_of_your_dataframe$north <- ifelse(name_of_your_dataframe$region == 'North',1,0) Estimate a model that drops all insignificant variables (at the 5% level) from the previous questions (Male dummy, all region dummies except for North). In this second model, which variables are significant at the 5% level? a. age b. bmi c. children d. tobacco e. North region dummy