In an experiment done in Ontario, Canada by entomologist Geoffery Beall, 72 independent blocks (areas to be sprayed) were created in tobacco fields and then 6 types of insect sprays were randomly assigned to the different blocks. The six different insect sprays were tested to see if there was a difference in the number of tobacco hornworms, Manduca quinquemaculata, found in the field after each spraying. This data set is already in R, just type in data(InsectSprays) and then attach(InsectSprays). Regardless of whether or not the Assumptions for the test are met, all parts below!!!

(a) Make a side-by-side boxplot showing the distribution for the number of insects for the different insect sprays. Comment on the results.

(b) Create residual plots for this data to check the normality and variability assumptions. Comment on what you see in the Residual vs. Fitted Plot and the Normal Q-Q Plot.

(c) Perform a Levene Test for Homogeneity of Variance. What can you conclude about the variation?

(d) State the null and alternative hypotheses for the one-way ANOVA on this data set.

(e) Perform the ANOVA on these data and show me your output table. What do you conclude?

(f) If the results of the ANOVA indicate that the means are significantly different, perform a multiple comparisons test (Tukey HSD confidence intervals) to determine which insect sprays differ in terms of the mean insect count. Analyze the differences and Interpret the first two significant intervals. Which of the insect spray(s) would you recommend if you want to kill the most tobacco worms?