13_Lecture13_ANOVA_Independent-Measures_0411r_Spring11

13_Lecture13_ANOVA_Independent-Measures_0411r_Spring11 -...

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1 PSY207 B Spring 2011 Psychological Statistics Introduction to ANOVA 13.1 Introduction An alysis o f Va riance (ANOVA) • To test for significant differences between means • How variable the group means are comparing to the grand mean • Compare the variability between groups to that within group • If we are only comparing two means, then ANOVA will give the same results as t-tests An alysis o f Va riance (ANOVA) •Two source of variability • Variability between groups • Variability within groups •F ratio • Variability between groups • Variability within groups • Random error An alysis o f Va riance (ANOVA) •Variance estimates • -Sum of squares •Between (SSbetween) •Within (SSwithin) •Total (SStotal) • -Mean squares (MS) •Multiple comparisons -Tukey HSD or Scheffe Group Measurement Dependent Variable Variable
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2 Group Measurement Independent Independent Variable Variable Quasi Quasi -Independent Independent Variable Variable Experiment Quasi-Experiment Measurement Factor 1 Factor 2 Factor The variable of the groups being compared. The variable can either be independent or quasi-independent. Factor The variable of the groups being compared. The variable can either be independent or quasi-independent. Measurement Factor 1 Factor 2 Levels The individual conditions or values that make up a factor. Levels The individual conditions or values that make up a factor. An alysis o f Va riance (ANOVA) • When we talk about an ANOVA, we specify • How many FACTORS are there in the analysis, for example • One-factor (one -way) ANOVA • Two-factor (two-way) ANOVA • How is each factor manipulated in the experiment • Between-subject / independent measures • Within-subject / repeated measures • How many levels are there in a factor Measurement Factor 1 Factor 2 2 X 2 factorial design 2 X 2 factorial design Group 1 Group 2 Group 3 Group 4 Time 2 Measurement Factor 1 2 X (2) factorial design 2 X (2) factorial design Group 1 Group 2 Time 1 Measurement Factor 2
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3 Introduction to ANOVA 13.1 Introduction 13.2 Example: One Factor, Independent Measures ANOVA 13.3 Components in ANOVA Example: One-Factor, Independent Measures Example: One-Factor, Independent Measures t test? •t test can’t be used to test more than two population means • T tests are based on differences between means • How do we test multiple differences at once? •We must develop a new inferential statistical test called…… ANOVA – test of null hypothesis for two or more population means ANOVA •Analysis • Breaking into constituent parts •Variance • Variation of scores about their mean •We’re going to break the variance into parts to test the null hypothesis One-Way ANOVA •One kind of ANOVA •Simplest •Used when population means differ on only one dimension • One factor with two or more levels
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4 One-Way ANOVA •Factor • Refers to an independent variable (IV) • In a one-way ANOVA, we have one factor • Two-way ANOVA: two factors…….
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This note was uploaded on 04/20/2011 for the course PSY 207 taught by Professor Pfordesher during the Spring '07 term at SUNY Buffalo.

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13_Lecture13_ANOVA_Independent-Measures_0411r_Spring11 -...

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