The story behind the data is as follows: The data are the results of an experiment to test whether directed reading activities in the classroom help elementary school students improve aspects of their reading ability. A treatment class of 21 third-grade students participated in these activities for eight weeks, and a control class of 23 third-graders followed the same curriculum without the activities. After the eight-week period, students in both classes took a Degree of Reading Power (DRP) test which measures the aspects of reading ability that the treatment is designed to improve. Original source: Schmitt, Maribeth C., The Effects on an Elaborated Directed Reading Activity on the Metacomprehension Skills of Third Graders, Ph.D. dissertaion, Purdue University, 1987.

- When you conducted your two-sample t-test in Homework 1, you had not looked at the data to see whether it was normal or if the sample size was large enough that some deviation from normality was all right. Do that now. Typically such analyses are not reported in detail in a scientific paper and should not typically be included in any project for this course. You simply do it before you decide what statistical test to employ to test your hypotheses. However, include your normal probability plots (quantile-quantile plots) in your report for this homework assignment.
- For the fun of it, also test whether the variances are equal between the treated and control groups. Since you most likely used a Welch's t-test, this is likely an unnecessary step in validating your previous analysis.

(2) There is no requirement to use R and the analysis will probabably be easier for most of you in Minitab. If you use R, good commands to look up include qqnorm and qqline. Note that R puts the sample on the y-axis and the normal distribution on the x-axis so that it flips what Minitab does unless you force R to flip it back. There is no need to flip it one way or the other, but you have to assess deviations from normality appropriately for the way you plot the data.

(3) The test of normality in R has command: shapiro.test. Look it up using the help command as described in Lab 1.

(4) Levene's test is not in base R. You have to first install and then load the "lawstat" package. Then, following Lab 1, the command would be:

levene.test(data[,2], data[,1])

Treatment Response Treated 24 Treated 43 Treated 58 Treated 71 Treated 43 Treated 49 Treated 61 Treated 44 Treated 67 Treated 49 Treated 53 Treated 56 Treated 59 Treated 52 Treated 62 Treated 54 Treated 57 Treated 33 Treated 46 Treated 43 Treated 57 Control 42 Control 43 Control 55 Control 26 Control 62 Control 37 Control 33 Control 41 Control 19 Control 54 Control 20 Control 85 Control 46 Control 10 Control 17 Control 60 Control 53 Control 42 Control 37 Control 42 Control 55 Control 28 Control 48