To: sbaker@odu.edu
From: Thomas Meyer
tmeyer@ph.vccs.edu
276 656-0283
Patrick Henry Community College
Subject: Statistics - w/ Dr.Spencer Baker - Homework Assignment #4, Ch 16 - Problem 20, page 440.
Date: April 12, 2004
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Question:
Use the same data as in Exercise 19 but conduct Tukey post hoc comparisons
instead of Scheffe. Are your conclusions different? If so, why does
this difference exist?
Answer:
Use the following algorithm:
1. Get the data
(Load career.sav)
2. Manipulate the data
Having loaded the data
Click Analyze menu
Compare Means
One-way ANOVA
Move the variable Mathfun to the Dependent List box
Move the variable Gradelvl to the Factor box
Click Post hoc
Click Scheffe
Click Tukey
Continue
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Oneway

This table displays the descriptive statistics for each group and for the
entire data set.
The left-hand column rows show the grade levels from 7th to 10th grades.
N indicates that there were 50 respondents in each group.
The Mean column shows the averages by grade level.
One-way ANOVA compares these sample estimates to determine if the population
means differ.
For ANOVA to be appropriate, the standard deviations should be similar to each
other, and this appears to be the case.
(Equaltiy could be inspected by using the Levene test.)
The lower and upper bounds contain the true value of the population mean 95% of
the time.

In one-way ANOVA, the total variation is partitioned into two components.
Between Groups represents variation of the group means around the overall mean.
Within Groups represents variation of the individual scores around their
respective group means.
Sig. indicates the significance of the F-test.
Small significance values (<.05) indicate group differences.
In this example, the significance level is less than .05. At least one of
the grade levels differs from the others.

This table lists the pairwise comparisons of the group means for all selected
post hoc procedures.
Mean difference lists the differences between the sample means.
Sig. lists the probability that the population mean difference is zero.
A 95% confidence interval is constructed for each difference. If this
interval contains zero, the two groups do not differ.
Notice that when 7th graders are compared with 8th graders, the Tukey test
does not contain zero, but the Sheffe does contain zero.
The Sheffe test is regarded as the more conservative test.
The asterisk shows those mean differences found to be significant at the .05
level.
For example, Tukey shows that 7th graders differ significantly with 8th and with
10th graders over perception of math as fun.
Scheffe, however, says that 7th graders differ significantly only with 10th
graders over perception of math as fun.
Said differently, 10th graders consider math less fun than 9th and 7th
graders. Data from both Tukey and Scheffe found these to be significant.
Seen from the 7th graders point of view, Scheffe found it significant that 7th
graders scored higher than 10th graders on Math is Fun.
But Tukey in examining the same 7th graders, found it significant that 7th
graders scored higher than both 8th and 10th graders. We conclude, that
the Scheffe test is more conservative, and "finds" fewer activities to be
significant according to the laws of chance.

In this figure, for all selected post hoc procedures, homogeneous groups are
defined.
These homogeneous groups are in columns 1, 2, and 3.
The means for each level of the independent variable are listed in their
corresponding group.
Homogeneous group 1 contains 10th and 8th graders in both the Tukey and
Scheffe.
Homogeneous group 2 contains 8th and 9th graders in Tukey, but 7th, 8th, and 9th
graders in Scheffe.
Homogeneours group 3 contains 9th and 7th graders in Tukey, but no grade levels
in Scheffe.
So the Scheffe and Tukey tests differ in whether or not there are three
homogeneous groups. The Scheffe is more conservative in saying that there
are but two homogeneous groups.
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filename: StatHW3Ch16Prob20page440TomMeyer.doc
Tom Meyer
Thomas Meyer