research methods advanced- week 6= two way anova

two-way anova

ANOVA basic idea

an analysis of variance, a parametric test that contains mean scores across conditions , 2+ conditions an extension of a t-test

factor

the independent vairable. in a study of the effect of type of drink on reaction time, type of drink would be the factor

level

the separate conditions present within the factor .

if we include caffinated coffee, decaf and water as three types of drink we can give our participants then out factor: drink type would have three levels

one-way ANOVA (single factor)

an anova with only one factor consisting of any number of levels. each level will require an independent sample- meaning: each level needs a different group of participants. for example one group that drinks caffinated coffee, one group that drinks decaf, and third one that drinks water .

ANOVA assumptions

homogeneity of variance, normally distributed data, your dependent variable should be continuous, your independent variable should consist of three or more categorical, independent groups

violating assumptions

when group sizes and equal ANOVA is robust enough to deal with violations of normality but not robust when you have unequal numbers

two way ANOVA’s statistics

produces main effect 1 and as well as a interaction effect. there will be 3 F values, one for each of the main effects and one for the interaction

steps in calculating a two way within subjects ANOVA

calculate descriptive statistics (means and SD), calculate and interpret the ANOVA (the two main effects, sphericity, the interaction) and post hoc tests

mauchly’s test

if significant: sphericity assumption violated

results

statistics will tell you which groups or conditions are statistically different from which, making sense of what that means is down to you make sure you look back at the descriptive statistics. use these to guide your interpretation