1. ANOVA EDL 714, Fall 2010

2. Analysis of variance  ANOVA  An omninbus procedure that performs the same task as running multiple t-tests between all groups in question.  Tests the null hypothesis in comparing means of two or more treatments (or populations)  Looking for systematic treatment effects

3. Two forms of variability  Between-treatments (groups)  Variability in scores/measures due to general differences between treatment conditions  Treatment effect, individual differences, experimental error  Within-treatments (groups)  Variability in scores/measures not associated with treatment  Individual differences, experimental error

4. Total variability  Is represented by accounting for both between and within group variability.  This is what an ANOVA is designed to do.  This reduces the risk of a Type I error over simply using multiple t-tests.

5. One-way ANOVA  Analyzes the effect of a single factor on between-group variability.  In ANOVA language, the independent variable is referred to as a factor. Hence, some researchers may use terms like Factor Analysis or Factorial Design when discussing ANOVA procedures.  A factor will have levels along which it varies.

6. One-way ANOVA in SPSS  Analyze  Compare Means  One-way ANOVA  In your output look for the Significance value (Sig.) just like you would on a t-test, and interpret the same way.  We will again use a.05 p value as our criteria for significance.  Note that in the ANOVA output box you will see a break-down of between group and within group variance.

7. Other forms of ANOVA  Two and Three-way ANOVAs  Multiple factors as opposed to one  Repeated Measures  Comparing means of the same samples over time  Analysis of Covariance (ANCOVA)  Multivariate Analysis of Variance (MANOVA)