For these practice problems, you will work with the cholesterol data set from the multcomp package that you should already have loaded. To load the data set and learn more about the study, use the following code:
require(multcomp)
data(cholesterol)
help(cholesterol)
2.1. Graphically explore the differences in the changes in Cholesterol levels for the five levels using boxplots and beanplots.
2.2. Is the design balanced?
2.3. Complete all 6+ steps of the hypothesis test using the parametric F-test, reporting the ANOVA table and the distribution of the test statistic under the null.
2.4. Discuss the scope of inference using the information that the treatment levels were randomly assigned to volunteers in the study.
2.5. Generate the permutation distribution and find the p-value. Compare the parametric p-value to the permutation test results.
2.6. Perform Tukey's HSD on the data set. Discuss the results - which pairs were detected as different and which were not? Bigger reductions in cholesterol are good, so are there any levels you would recommend or that might provide similar reductions?
2.7. Find and interpret the CLD and compare that to your interpretation of results from 2.6.
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