Lecture 13 Factorial ANOVA II

Lecture 13 Factorial ANOVA II - Factorial ANOVA Part 2...

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    Factorial ANOVA Part 2 Lecture 13
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    Today More on Factorial ANOVA How to do calculations Working with the ANOVA source table Following up on results Tukey’s HSD Graphing mean values
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    Factorial ANOVA Factorial ANOVA is an experimental design with two or more independent variables Factor = independent variable Each variable can have two or more levels An advantage: we can look at the effect of each variable , AND the interaction between the two variables
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    Factorial ANOVA Design Factor A Row Means A1 A2 A3 Factor B B1 Scores on A 1 B 1 1 ) Scores on A 2 B 1 2 ) Scores on A 3 B 1 3 ) µ b1 B2 Scores on A 1 B 2 4 ) Scores on A 2 B 2 5 ) Scores on A 3 B 2 6 ) µ b2 Column Means µ a1 µ a2 µ a3 µ grand
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    American Idol Example  Factorial ANOVA Research Question: do mean scores for American Idols differ based on attractiveness and gender? Attractive Okay Unattractive Male A 1 B 1 1 ) A 2 B 1 2 ) A 3 B 1 3 ) Female A 1 B 2 4 ) A 2 B 2 5 ) A 3 B 2 6 )
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    American Idol Example: Data Attractiveness (A) Attractive Okay Unattractive Gender (B) Male 1 2 1 4 5 6 6 4 4 Female 8 9 10 5 6 6 1 2 3
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    What questions can we ask? Research Question 1: general Are there any mean differences between each group? Research Question 2: main effect #1 Are there mean differences between levels for IV1? Research Question 3: main effect #2 Are there mean differences between levels for IV2? Research Question 4: interaction Are there mean differences between levels for IV1 depending on levels for IV2?
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    Idol example: Research questions Research Question 1: general Are there any mean differences between each group on American idol scores? Research Question 2: main effect #1 Does attractiveness level matter to mean scores? Research Question 3: main effect #2 Does gender matter to mean scores? Research Question 4: interaction Does the score for gender depend on how attractive the person is?
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    For each research question,  there is… A null hypothesis An alternative hypothesis A calculated test statistic A critical value that must be compared to calculated value A conclusion
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    In each case, the null hypothesis (H 0 ) says there is no difference between the groups. The alternative hypothesis (H a ) says that there is a difference.
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    Hypotheses: Question 1 H 0 : There are no differences in mean rating scores based on attractiveness or gender. H o : µ attractive male = µ attractive female = µ unattractive male = µ unattractive female H a : At least one of the group means differ from the others.
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  Hypotheses: Question 2 H 0 : There is no difference in American idol mean scores based on attractiveness. H
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This note was uploaded on 05/25/2010 for the course PSYC 11 taught by Professor Ryne during the Spring '10 term at UC Riverside.

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Lecture 13 Factorial ANOVA II - Factorial ANOVA Part 2...

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