Research Methods IV - Week 7 Factorial ANOVA I

That this experiment has 2 IV's. Two of them have three levels

That this experiment has 3 levels. Two of them have 3 IV's and one has two

That this experiment has 3 IV's. Three of them have 3 levels

That this experiment has 3 IV's. Two of them has 3 levels and one has two.

We can see the main effects of each DV

We can see the main effects of each IV, and how they interact

We can see the main effects of each DV, and how they interact

We can see the main effects of each IV

You cannot further split the variance explained by SSm

The variance explained by SSm is made up of only the SS for each variable

The variance explained by SSm is made up of the SS for each variable plus the SS for the interactions

The variance explained by SSm is made up of the MS for each variable plus the MS for the interactions

We average across all levels of gender and only look at the differences in age groups

We average across all levels of age and only look at the differences in age group

We average across all levels of age and only look at the different levels of gender groups

We average across all levels of gender and only look at the differences in gender

After calculating SSage and SSgender then the remaining variance accounted for by SSt is the variance from SSage*gender. This is the interaction between the two variables

After calculating SSage and SSgender then the remaining variance accounted for by SSm is the variance from SSage*gender. This is the main effect of the two variables

After calculating SSage and SSgender then the remaining variance accounted for by SSm is the variance from SSage*gender. This is the interaction between the two variables

You do not get SSage*gender in independent samples factorial ANOVA

When both IV's have a main effect

When the effect of one DV on the IV is dependent on another DV

When the effect of one IV on the DV is dependent on another IV

When both DV's have a main effect

Colour perception improvement with age did not differ both boys and girls. For both genders, colour perception was better for 11 year olds compared to five year olds.

Colour perception improvement with age differed between boys and girls. For boys, no difference in colour perception was found between 5 year olds and 11 year olds. However, for girls there was an effect of age on colour perception.

Colour perception improvement with age did not differ both boys and girls across the ages. For both genders, colour perception was better for 5 year olds compared to 11 year olds.

Colour perception improvement with age differed between boys and girls. For girls, no differences in colour perception were found between 5 year olds and 11 year olds. However, for boys there was an effect of age on colour perception.

Homogeneity of variance; the Levene's test should not be significant.

Sphericity; the Mauchly's test should be significant.

Sphericity; the Mauchly's test should not be significant.

Homogeneity of variance; the Levene's test should be significant.

Because we want to examine the differences between the IV's

To understand the effects of the individual variables

You don't need to do this as it shows the same as the main effects

Because this is the best way to explain an interaction, if the interaction exists.

Because we don't just need to know how much variance is explained by the model, but whether each individual variable and their interactions is explaining a significant amount of the variance

Because we need to know how much variance is explained by the SSr output, which is part of the variance explained by SSm

Trick question - we only interpret the SSm line of output in factorial ANOVA

Because we don't just need to know how much variance is explained by the model, but whether each individual variable is explaining a significant amount of the variance