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Stat 302 – Day 20

Stat 302 – Day 20. Review. Overview. Comparing two means Validity conditions Equal variance condition Confidence intervals Effect size: (diff in means)/SD Comparing several means Choice of statistic (e.g., MAD) F-statistic  ANOVA (validity conditions)

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Stat 302 – Day 20

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  1. Stat 302 – Day 20 Review

  2. Overview • Comparing two means • Validity conditions • Equal variance condition • Confidence intervals • Effect size: (diff in means)/SD • Comparing several means • Choice of statistic (e.g., MAD) • F-statistic  ANOVA (validity conditions) • Follow-up analysis (simultaneous CIs) • Effect size: R2

  3. Overview • Statistical models (ways to predict response) • Model equation • Treatment effects vs. Group means • Residual analysis • Multiple explanatory variables (“factors”) • Effect of Variable 1 after adjusting for variable 2 • Treatment variables vs. blocking variables • Additive models (mean + A effect + B effect) • Interactions (difference in treatment effects of one variable depending on value of second variable)

  4. Overview • Randomization test with block designs • Comparing nested models • Separate means vs. Two means • Comparison of SSE values

  5. Terminology - Treatment • If one explanatory variable, the treatments are the categories of that variable • If two treatment variables, then the treatments are all the possible combinations of the categories for the 2 variables • If one treatment variable and one blocking variable, the treatments are the categories of the treatment variable

  6. Terminology - Effect

  7. Example • Lots of variation in ratings given to job candidates • How much of that variation is “due to” type of disability? Males Females

  8. Example • The effect of antibiotic depends on whether or not is taken Vitamin B12

  9. The additive model • Our data

  10. Including the interaction term

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