1/19/2018

Chapter 0

Introduction to a randomization/permutation test
Open Day1.csv (data from the first day of a data analysis course) The variables are:
- Pulse 1 - resting pulse
- Pulse2 - pulse after 1 minute of exercise
- Gender
- Distance - distance traveled from home to campus
- Diff = Pulse2 - Pulse1
Is the mean increase in pulse after exercise different for men and women?
To answer this question we will consider a completely different type of inference, based on randomization.
Simple demonstration of the idea with cards
Open StatKey and click Test for Difference in Means
- Upload the file Day1.csv
- Generate 1 sample
- Generate 1000 samples
- Make Inference
Compare inference based on this simulation technique with the inference from t.test (see Day1.R)

Importing scripts - open Day1.R
Subsetting in R - try the subset command
- female <-subset(mydata, Gender=='F')
Try to access and save a file to your HW folder GoogleDrive:\Stat206-S2018\yourname

Compare the resting pulses of men and women
Compare the active pulses of men and women
Compare the distrance traveled to Gambier for men and women
Create a new varaiable, say Diff, to measure the increase in pulse after one minute of exercise. Do the heart rates for men increase more than the heart rates for women after one minute of exercise?
Exercise 0.17 on p. 20
Exercise 0.14 with a randomization/permutation test