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This Concept Map, created with IHMC CmapTools, has information related to: Project 3, Key take away points: *Independent vs. Dependent variables *Descriptive vs. Inferential statistics *Continuous variables vs. categorical variables *Type I vs. Type II errors Midterm exam: worth 1/3 of overall grade, Key take away points: * mixed ANOVA is also known as a mixed plot design *both effects are fixed in mixed ANOVA Midterm exam: worth 1/3 of overall grade, Week 6: Mixed ANOVA Between vs within subjects design, Theory of RM ANOVA Key take-away points: *RM ANOVA is when the same or matched participants serve in two treatment conditions (e.g., pre- and post-tests) * RM ANOVA is also known as Within-subjects design *sphericity is the variances of difference scores between each pair of treatment levels are equal *Use Bonferroni when doing a post hoc pairwise comparison in SPSS, Mean comparison Key take-away points: *RM ANOVA is when the same or matched participants serve in two treatment conditions (e.g., pre- and post-tests) * RM ANOVA is also known as Within-subjects design *sphericity is the variances of difference scores between each pair of treatment levels are equal *Use Bonferroni when doing a post hoc pairwise comparison in SPSS, Theory of mixed ANOVA Key take away points: * mixed ANOVA is also known as a mixed plot design *both effects are fixed in mixed ANOVA, Assumptions Key take-away points: *RM ANOVA is when the same or matched participants serve in two treatment conditions (e.g., pre- and post-tests) * RM ANOVA is also known as Within-subjects design *sphericity is the variances of difference scores between each pair of treatment levels are equal *Use Bonferroni when doing a post hoc pairwise comparison in SPSS, Week 4: Two-way ANOVA Interaction effects, Week 3: Multiple Comparison Procedures Pairwise familywise, Week 3: Multiple Comparison Procedures Week 4: Two-way ANOVA, Key take away points: *Family-wise Type 1 error rate is the probability of committing at least one Type I error in the family of contrasts/tests *Post Hoc multiple comparison procedures in SPSS examine (only) all pairwise comparisons of means *Always refer to APA 6th edition for write-up information Midterm exam: worth 1/3 of overall grade, Key take away points: * mixed ANOVA is also known as a mixed plot design *both effects are fixed in mixed ANOVA Summative Assessment: Analyzing the learning over a six-week period in EDUC 409, A week-long review of weeks 1-6 of EDUC 409: Analysis of Experimental Data Week 6: Mixed ANOVA, Statistics Key take away points: *Independent vs. Dependent variables *Descriptive vs. Inferential statistics *Continuous variables vs. categorical variables *Type I vs. Type II errors, Theory of One-way ANOVA Key take away points: *Use One-way ANOVA to compare only two or more means *Use the "General Linear Model" in SPSS to run One-way ANOVA *Effect size is only for significant findings (look at F value) to show how the findings can be used in the real world *Assumption test shows independence, normality, and homogenity of variance, Key take away points: *Family-wise Type 1 error rate is the probability of committing at least one Type I error in the family of contrasts/tests *Post Hoc multiple comparison procedures in SPSS examine (only) all pairwise comparisons of means *Always refer to APA 6th edition for write-up information Key take away points: *Run Two-way ANOVA when there is only one DV and several IVs *a Two-way factorial ANOVA has 2 factors while a Three-way factorial ANOVA has 2x3x3 *Two-way ANOVA decreases the error rate *Caution: if the interaction effect size is small relative to a main effect, don't over interpret the interaction effect, Key take away points: *Run Two-way ANOVA when there is only one DV and several IVs *a Two-way factorial ANOVA has 2 factors while a Three-way factorial ANOVA has 2x3x3 *Two-way ANOVA decreases the error rate *Caution: if the interaction effect size is small relative to a main effect, don't over interpret the interaction effect Midterm exam: worth 1/3 of overall grade, Key take away points: *Use One-way ANOVA to compare only two or more means *Use the "General Linear Model" in SPSS to run One-way ANOVA *Effect size is only for significant findings (look at F value) to show how the findings can be used in the real world *Assumption test shows independence, normality, and homogenity of variance Key take away points: *Family-wise Type 1 error rate is the probability of committing at least one Type I error in the family of contrasts/tests *Post Hoc multiple comparison procedures in SPSS examine (only) all pairwise comparisons of means *Always refer to APA 6th edition for write-up information, Week 4: Two-way ANOVA Week 5: Repeated-measures ANOVA, Week 6: Mixed ANOVA Theory of mixed ANOVA