Homework 3

1. The provided code splits the body temperature data into two groups by sex. Use this data to do the following.

   1. Compute a 90% confidence interval for the mean female body temperature and interpret the interval in context in the style introduced in class.
   2. Compute a 90% confidence interval for the mean male body temperature and interpret the interval in context in the style introduced in class.
   3. Based on your intervals, is it plausible that there is no difference in mean temperature by sex? Why or why not?

Solution

load('data/temps2.RData')

# split observations into two groups by sex
temps.split <- split(temps$body.temp, temps$sex)

# store male and female temperatures
temps.m <- temps.split$male
temps.f <- temps.split$female

# part a: confidence interval for mean body temps for female

# part b: confidence interval for mean body temps for male

1. [your answer here]
2. [your answer here]
3. [your answer here]

2. Find the dataset that contains the measurements we took in class.

   1. Construct a histogram of the measurements and describe its shape.
   2. What value(s) would be considered unusual? Explain.
   3. Find your measurement (clicking the dataset in your environment will open the data table in a viewer window). Which quartile of the class are you in?
   4. Pretend that our class is a representative sample of adults. Compute and interpret a 95% confidence interval for the mean.

Solution

# load armspan data

# part a: construct a histogram

# part b: what value(s) would be unusual? (hint: consider the SD)

# part c: find your measurement and compute percentile

# part d: confidence interval for population mean

1. [your answer here]
2. [your answer here]
3. [your answer here]
4. [your answer here]