Microsoft Office Tutorials and References
In Depth Information
Chapter 8
One-Way Analysis of Variance (ANOVA)
So far in this 2010 Excel Guide, you have learned how to use a one-group t-test to
compare the sample mean to the population mean, and a two-group t-test to test for
the difference between two sample means. But what should you do when you have
more than two groups and you want to determine if there is a significant difference
between the means of these groups?
The answer to this question is: Analysis of Variance (ANOVA).
The ANOVA test allows you to test for the difference between the means when
you have three or more groups in your research study.
Important note:
In order to do One-way Analysis of Variance, you need to have
installed the ‘‘ Data Analysis Toolpak’’ that was described in
Sect. 6.5.1 . If you did not install this, you need to do that now.
Let’s suppose that you wanted to study the sound bursts of three subspecies of
forager honey bees in relation to a food source that was 400 m from their hive.
These honey bees ‘‘dance’’ by producing sound bursts in a cycle, and the
researchers have obtained the average number of sound bursts per cycle for these
bees. The hypothetical results are given in Fig. 8.1 . Is there any evidence that these
three subspecies of honey bees produce a different number of sound bursts per
cycle?
You have been asked to analyze the data to determine if there was any
significant difference in the average number of sound bursts per cycle between the
three subspecies of honey bees. To test your Excel skills, you have selected a
random sample of bees from each of these subspecies (see Fig. 8.1 ). Note that each
subspecies can have a different number of bees in order for ANOVA to be used on
the data. Statisticians delight in this fact by referring to this characteristic by
stating that: ‘‘ANOVA is a very robust test.’’ (Statisticians love that term!)
T. J. Quirk et al., Excel 2010 for Biological and Life Sciences Statistics,
DOI: 10.1007/978-1-4614-5779-4_8,
Springer Science+Business Media New York 2013
165
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