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TWO-WAY BETWEEN-SUBJECTS ANOVA

TWO-WAY BETWEEN-SUBJECTS ANOVA. What is the Purpose?. Determine whether there are significant main effects and a significant interaction. Use for a between-subjects factorial design. What are the Assumptions ?. Independent observations Interval or ratio level data

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TWO-WAY BETWEEN-SUBJECTS ANOVA

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  1. TWO-WAY BETWEEN-SUBJECTS ANOVA

  2. What is the Purpose? Determine whether there are significant main effects and a significant interaction. Use for a between-subjects factorial design.

  3. What are the Assumptions? • Independent observations • Interval or ratio level data • Normal distribution of DV • Homogeneity of variance (or proportional cell sizes)

  4. How Does it Work? • As in any ANOVA, variance is divided into parts and then the parts are compared. • Three F-tests are computed: • Main effect of Factor A • Main effect of Factor B • A x B interaction

  5. Dividing the Variance • Total variance is divided into Between Groups and Within Groups • Between Groups variance is subdivided into three parts: • Factor A • Factor B • A x B interaction

  6. Dividing the Variance • Each part of the Between Groups variance can be affected by: • Effect (A, B, or A x B): systematic • Individual differences: non-systematic • Measurement error: non-systematic • Within Groups variance can be affected by: • Individual differences: non-systematic • Measurement error: non-systematic

  7. Comparing the Variance • Each F-test is the ratio between variance for the effect (numerator) and Within Groups variance (denominator)

  8. Comparing the Variance

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