Microsoft Office Tutorials and References
In Depth Information
The answer to this question is analogous to the decision rule used in this topic for
both the one-group t-test and the two-group t-test . You will recall that this rule (See
Sect. 4.1.6 and Sect. 5.1.8) was:
If the absolute value of t is less than the critical t, you accept the null hypothesis.
or
If the absolute value of t is greater than the critical t, you reject the null hypothesis,
and accept the research hypothesis.
Now, here is the decision rule for ANOVA:
Objective : To learn the decision rule for the ANOVA F-test
The decision rule for the ANOVA F-test is the following:
If the value for F is less than the critical F-value, accept the null hypothesis.
or
If the value of F is greater than the critical F-value, reject the null hypothesis, and
accept the research hypothesis.
Note that Excel tells you the critical F-value in cell G31: 3.32
Therefore, our decision rule for the honey bees AVOVA test is this:
Since the value of F of 8.19 is greater than the critical F-value of 3.32, we reject the
null hypothesis and accept the research hypothesis.
Therefore, our conclusion, in plain English, is:
There is a significant difference between the average number of sound bursts per
cycle between the three subspecies of honey bees.
Note that it is not necessary to take the absolute value of F of 8.19. The F-value
can never be less than one, and so it can never be a negative value which requires us
to take its absolute value in order to treat it as a positive value.
It is important to note that ANOVA tells us that there was a significant difference
between the population means of the three groups, but it does not tell us which pairs
of groups were significantly different from each other .
8.4 Testing the Difference Between Two Groups
using the ANOVA t-test
To answer that question, we need to do a different test called the ANOVA t-test.
Objective : To test the difference between the means of two
groups using an ANOVA t-test when the ANOVA
results indicate a significant difference between
the population means.
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