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2-Way Mixed Analysis of Variance

2-Way Mixed Analysis of Variance. Women’s PBA - 2009. Data Description. Women’s Professional Bowling Association – Qualifying rounds at Alan Park, Michigan (2009). Factors: A: Oil Pattern (Fixed) with a=4 levels: 1=Viper, 2=Chameleon, 3=Scorpion, 4=Shark

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2-Way Mixed Analysis of Variance

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  1. 2-Way Mixed Analysis of Variance Women’s PBA - 2009

  2. Data Description • Women’s Professional Bowling Association – Qualifying rounds at Alan Park, Michigan (2009). • Factors: • A: Oil Pattern (Fixed) with a=4 levels: • 1=Viper, 2=Chameleon, 3=Scorpion, 4=Shark • B: Bowler (Random) with b=15 levels: • 1=DiandraAbaty, 2=ShalinZulkiffi, 3=Liz Johnson, 4=Kelly Kulick, 5=Clara Guerrero, 6=Jennifer Petrick, 7=Wendy MacPherson, 8=Shannon Pluhowski, 9=Stephanie Nation, 10=Tammy Boomershine, 11=Amanda Fagan, 12=Aumi Guerra, 13=Michelle Feldman, 14=Shannon O'Keefe, 15=Jodie Woessner • Replicates: Each bowler rolled 2 sets of 7 games on each pattern (Y = Total Pins in a game, n=14)

  3. Statistical Model

  4. Covariance Structure / ANOVA (Unrestricted Model)

  5. Expectations and Variances of Means - I

  6. Expectations and Variances of Means - II

  7. Expected Mean Squares - I

  8. Expected Mean Squares - II

  9. Expected Mean Squares III & F-Tests

  10. Bowling Results (a=4, b=15, n=14)

  11. Estimating Population Mean Score

  12. Simple Effects – Comparing Oil Patterns Within Bowlers

  13. Marginal Effects – Comparing Oil Patterns Across Bowlers

  14. Pairwise Comparisons Among Oil Patterns

  15. Estimating Variance Components

  16. Output from SAS PROC MIXED

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