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Analysis of variance
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Univariate = one way
Multivariate = two or more ways (two or more separate variables which can each divide sample into two groups)
ANOVA can be used instead of T Test, even if only 2 levels, but should always be used for 3 or more groups
Interaction = does the effect of one variable affect the other?
On plots = the steeper the line, the bigger the effect
If lines are parallel = no significant interaction
Plots show where interaction is (in what direction); test figures only say how big it is
Main effect (eg time or weather) = difference between average time/weather of one one variable compared to other
Interaction = difference between differences
To run a contrast = insert following before /method; /contrast(variable name) = special (.....) - contrast weights
Scheffe (post-hoc) - use same procedure as normal, inc contrasts but ignore significance.
Scheffe criterion = (K-1) x Tabled value of Fk-1, error df
where K = number of levels in factor being examined
error df = degrees of freedom of demonimator from table
If F = higher than scheffe criterion answer it is significant
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- Stats (Univariate ANOVA) Notiz am Analysis of variance, erstellt von Sarah Windsor am 22/04/2013.
- Erstellt von
- Sarah Windsor · Apr 2013
- Aktualisiert
- 19 Feb 2016
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