I will discuss some of the assumptions, explain the logic behind the statistics and show a quick way of calculating the repeated measures ANOVA,
In the previous post I discussed ANOVA for unrelated samples, which is an equivalent of a t-test for unrelated samples. Similarly, within-subjects ANOVA is an equivalent of a t-test for related samples. However, as I stated before, both ANOVAs can be used for comparing more than just two samples.
I will discuss some of the assumptions, explain the logic behind the statistics and show a quick way of calculating the repeated measures ANOVA,
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ANOVA is a statistics test which, exactly like a t-test, compares sample means to see whether the difference between these samples is statistically significant. However, unlike t-tests, ANOVA can be used to compare not only 2, but 3 or more samples - in fact, as many as you like! Also like with the t-test, there is ANOVA test for unrelated and related samples. In this post, I will only discuss the unrelated-subjects design: that is, when all the participants are tested only once. ANOVA can also be two-ways, three-ways etc. - depending on how many independent variables there are in an experiment. Today I will look at the one-way ANOVA, which works with one IV. As always, I will cover the assumptions, logic behind the test and show step-by-step calculation using an example. |
AuthorI am a 21 years old Psychology undergraduate in Edinburgh University. The idea behind this site is to provide some help to fellow students, to make studying psychology (including stats...) as much fun as possible and motivate me not to skip those 9am lectures! Archive
February 2013
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