Anova: two way & interactions - Tutorial
7 important questions on Anova: two way & interactions - Tutorial
What are the consequences of continuing a GLM in the case that the variances are unequal?
- the power of your test reduces
- the chance of committing a Type II error increases
- it would rapidly lead to accepting your null hypothesis; there is no difference
Can an anova be used for cases where you have 2 groups?
Can non parametric tests be used for cases where you have a normal distribution in your data?
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How many null-hypothesis are you testing when you have an anova with 2 independent variables?
- 2 per variable
- interaction between the 2 variables
- intercept (regression)
- There is no difference in starling masses between sexes
- There is no difference in staling masses between seasons
- There is no interaction effect of sex and season of body mass
- The intercept is not equal to zero
If you do a one-way anova twice, instead of a 2-factor anova once, which error are you making?
Why if you are working with large datasets can the test for normality can not be trusted?
What do you do when you are working with large datasets?
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