Analysis of Variance
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| Inflation of Type I Error | show 🗑
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| show | Compares multiple pop. means that avoids the inflation of type I error rates. Test one null hypothesis to determine if any of the pop. mean differ from the rest. Type I error remains at alpha. Use w/ interval/ratio data.
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| One-Factor ANOVA | show 🗑
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| Independent Sample ANOVA Assumptions | show 🗑
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| show | Pool all the sample variances. When the sample sizes are the same the pooled variance is the average of the individual sample variances. DF=N-k N:total # of obs. k:# diff. pop. Good estimate of pop. variance when null is correct & incorrect.
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| show | Based on the sample means. DF=k-1. Good estimate of pop. variance only when null is correct.
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| show | MSW is based on variability w/n each sample. MSA only good when all sample means can be considered from same pop. If null is true, MSA & MSW should be similar & ratio should be close to 1.
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| Partitioning the Sum of Squares | show 🗑
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| show | Goal is to decide if there is a difference among the dependent pop. means. Randomized complete block (two-way) & repeated measures. MST has k-1 df & MSE has N-k-b+1 df. SSB has b-1 df. SST has N-1 df.
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| Dependent Samples Assumptions | show 🗑
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horsenerd09
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