Cramming Sam's top tips from chapter 14

Click on the topic to read Sam's tips from the book

Factorial ANOVA

  • Two-way independent designs compare several means when there are two independent variables and different entities have been used in all experimental conditions. For example, if you wanted to know whether different teaching methods worked better for different topics, you could take students from four courses (Psychology, Geography, Management, and Statistics) and assign them to either lecture-based or book-based teaching. The two variables are topic and method of teaching. The outcome might be the end-of-year mark (as a percentage).
  • In the table labelled Tests of Between-Subjects Effects, look at the column labelled Sig. for all main effects and interactions; if the value is less than 0.05 then the effect is significant using the conventional criterion.
  • To interpret a significant interaction, plot an interaction graph and conduct simple effects analysis.
  • You don’t need to interpret main effects if an interaction effect involving that variable is significant.
  • If significant main effects are not qualified by an interaction then consult post hoc tests to see which groups differ: significance is shown by values smaller than 0.05 in the columns labelled Sig., and bootstrap confidence intervals that do not contain zero.
  • Test the same assumptions as for any linear model (see Chapter 6).