General Questions. 
 How is data dredging or data snooping different from performing
multiple comparison procedures?
 The equation below provides a 95% confidence interval for the difference
between two population means. What is the s_{p} term and how
is it estimated?
 Consider the following equations. Indicate with a check in the appropriate
box which are true linear contrasts.
Equation 
Contrast 
Not Contrast 












 Is equation l_{1} above orthogonal to l_{2}?
 In problem 8.12, page 416, Ott and Longnecker describe a strawberry
preservation study involving three preservatives and a no treatment
control. This resulted in four treatment groups (t=4), denoted (Control,
A, B, C). Assume the four sample means are given by respectively.
For each of the following questions write a linear contrast in the
four means that would be used to answer the question.
 Q1: Is Treatment A different from the notreatment Control?
 Q2: Is the average of treatments A, B and C different from the
notreatment control?
 Q3: Is Treatment A different from Treatment C?
 Q4: Is the average of Treatments A and B different from Treatment
C?
 In the discussion of individual comparison Type I error rates and
experimentwise Type I error rates an equation is given which describes
the relationship between the two. Suppose we have t=9 treatments and
we wish to look at all t(t1)=m=72 individual contrasts. What value
should we use for the individual comparison Type I error rate (a_{I})
to achieve an overall error rate of a_{E}=0.05?
 Which of the following multiple comparison procedures are most conservative
(in the sense that one is least likely to make a Type I experimentwise
error)?
 Fisher's LSD
 StudentNewmanKeuls
 Tukey's W
 Duncan's MCP
 WallerDuncan

For
students in agriculture and environmental fields. 
 Using the data and analysis from the previous exercise (Unit 3 Section
1), perform a multiple comparison analysis, with experimentwise Type
I error rate of 0.05, using each of the following procedures:
 Fisher's LSD
 StudentNewmanKeuls
 Tukey's W
 Duncan's MCP
 WallerDuncan
If you transformed the data prior to the analysis of variance, the
multiple comparison procedures should be performed on the transformed
data as well.
 Using these same data, test the contrast
where t=1 for variety A, t=2 for variety B, etc.

For
students in engineering fields. 
 Using the data and analysis from the previous exercise (Unit 3 Section
1), perform a multiple comparison analysis, with experimentwise Type
I error rate of 0.05, using each of the following procedures:
 Fisher's LSD
 StudentNewmanKeuls
 Tukey's W
 Duncan's MCP
 WallerDuncan
If you transformed the data prior to the analysis of variance, the
multiple comparison procedures should be performed on the transformed
data as well.
 Using these same data, test the contrast
where t=1 for Machine_C, t=2 for Machine_B, t=3 for Machine_A.

For
students in toxicology and health science fields. 
 Using the data and analysis from the previous exercise (Unit 3 Section
1), perform a multiple comparison analysis, with experimentwise Type
I error rate of 0.05, using each of the following procedures:
 Fisher's LSD
 StudentNewmanKeuls
 Tukey's W
 Duncan's MCP
 WallerDuncan
If you transformed the data prior to the analysis of variance, the
multiple comparison procedures should be performed on the transformed
data as well.
 Using these same data, test the contrast
where t=1 for group A, t=2 for group B, etc.

For
students in community development, education and social services fields. 
 Using the data and analysis from the previous exercise (Unit 3 Section
1), perform a multiple comparison analysis, with experimentwise Type
I error rate of 0.05, using each of the following procedures:
 Fisher's LSD
 StudentNewmanKeuls
 Tukey's W
 Duncan's MCP
 WallerDuncan
If you transformed the data prior to the analysis of variance, the
multiple comparison procedures should be performed on the transformed
data as well.
 Using these same data, test the contrast where
t=1 for age group A, t=2 for age group B, t=3 for age group C.
