To accomplish this task, you need to do the following:

1. For each variable in the data set, identify what type of variable it is:

Variable	Type of Variable (Categorical or Quantitative)
Sex	Categorical
Systolic Blood Pressure (sbp)	Quantitative
Diastolic Blood Pressure (dbp)	Quantitative
Age	Quantitative
Body Mass Index (bmi)	Quantitative
Coronary Heart Disease (chdfate)	Categorical

1. For the categorical variables, fill in the following table (you may need to add more rows):

Variable	Categories	Percent, (n)
Sex	Male = 1	2049
Sex	Female = 2	2650
CHD	Otherwise = 0	3226
CHD	Patient developed CHD at follow-up = 1	1473

1. For the quantitative variables, fill in the following table (you may need to add more rows):

Variable	Mean +/- sd
sbp	132.7 +/- 22.8
dbp	82.5 +/- 12.7
age	46.0 +/- 8.5
bmi	25.6 +/- 4.0

1. How would you determine if values are outliers for a particular variable?
   1. Does the variable for body mass index have any outliers?
   2. How might these outliers affect the mean for body mass index?

1. For each of the categorical variables, find mean and standard deviation of body mass index and enter values in the table below (you may need to add more rows):

Variable	Categories	n	Mean +/- sd
Sex	Male = 1	2047	25.9 +/- 3.3
Sex	Female = 2	2643	25.3 +/- 4.5
CHD	Otherwise = 0	3218	25.1 +/- 4.0
CHD	Patient developed CHD at follow-up = 1	1472	26.5 +/- 4.1

Based on the table above, does it appear that any of the variables are related to body mass index (check to see if the means are different between categories for a particular variable)?

What methods could you use to see if a quantitative variable is related to body mass index? Use one of those methods to determine which (if any) of the quantitative variables is related to body mass index. Which of the quantitative variables is related to body mass index?Justify your answer https://1drv.ms/x/s!ApAjhIcc8n1EgVUs2k_pAxqWFzly?e=Kmwjke