STAT 705 Spring 2017
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Homework 4
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22.1, 22.6, 22.9(b,c), 22.10(a,b,c,d,f), 22.23,
26.2, 26.4, 26.5(c,d,e,f), 27.3(c,d), 27.4(a,b,c), 27.22, and this extra problem:

EXTRA PROBLEM:  Look at the "store displays" data from problem 27.13.  
Use PROC MIXED to determine the best covariance structure for the repeated measurements within stores.
Based on the best model choice, test for display*time interaction, and if appropriate, 
for display effects and time period effects.  Give P-values for your tests.

NOTE: For 22.9(b), do the residual plot (vs. fitted values), 
the normal Q-Q plot, and the Shapiro-Wilk test (and state your
conclusions).

NOTE: For 22.10(c), you don't have to fit the full and reduced 
models separately if you let SAS or R do the appropriate F-test.

HINT:  For 22.10(f), to decide which is "more efficient", compare 
(22.18) to the square root of (22.17) on page 930.

HINT:  For 22.23, note that you are deriving the LS estimator 
for ANY PARTICULAR delta_i.  So if you want, you could derive 
it for delta_1, and then just generalize your result.  In any 
case, note that in #22.23 you will be solving two equations 
with two unknowns.

NOTE: For 26.4(b), show the residuals plotted for each machine
level, and state your conclusions.

NOTE:  For 27.4(c), use the Tukey procedure to compare all pairs of dose levels, 
rather than the Bonferroni method as the book describes.

The "Auditor Training", "Auditor Training #21.13", "Detergent Effectiveness", 
"Hardware Sales", "Telephone Communications" and "Questionnaire Color #22.9"
data sets are given on the course web page. 

The "Muscle Mass", "Bottling Plant Production", "Blood Pressure/Rabbit", and "Store Displays" data sets 
are given on the course web page.

Please write your answers neatly and clearly!