Question

Describe the key difference between the separation of between treatment variability for the one-factor independent measures ANOVA and the two-factor independent measures factorial ANOVA.

Answer 1

In a one-way ANOVA there are two possible hypotheses.

1)The null hypothesis (H0) is that there is no difference between the groups and equality between means.

2lThe alternative hypothesis (H1) is that there is a difference between the means and groups.

Assumption of one way anova

1)Normality – That each sample is taken from a normally distributed population

2)Sample independence – that each sample has been drawn independently of the other samples

3)Variance Equality – That the variance of data in the different groups should be the same

4)Your dependent variable – here, “weight”, should be continuous – that is, measured on a scale which can be subdivided using increments (i.e. grams, milligrams)

Two factorial ANOVA

Two way factorial ANOVA is a special case of factorial ANOVA.

1)“Two way” refers to the number of factors in a factorial ANOVA design. A two way ANOVA would have a factor A (with 2 or more levels or groups) ‘crossed with’ a factor B (also with 2 or more levels or groups.

2)Factorial designs can have more than 2 factors. If you have three factors (A, B and C) this is called a three way factorial.

3)Factorial ANOVA adds any number of categorical IVs to the regression (and maybe some interactions among them).