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Lecture 11

Lecture 11 – Comparing several means - summary page.docx

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University of Waterloo
SOC 280
Owen Gallupe

1 Lecture 11 – Comparing Several Means – Summary Page - ANOVA – tell you whether the average score on a particular variable is significantly different across three or more groups. -t-tests: for comparing means of two groups -ANOVA: for comparing means of 3+ groups  ie do 3 gen immigrants get better jobs than 1 or second gens?  Ie do cancer patients who take a new medication get better results than with other drugs, no drugs, or alternative therapy. -Asking if theres differences between groups. -Why cant I run multiple T tests? • Have a risk of 5% being wrong with our test, so if we do another t test with another p value then we have an additional 5% chance of being wrong. Every time you do a new T-test you’re increasing your likelihood for error. a. Assumptions i. Normality 1. To check for it, look at the histogram for our DV and look at skewness/kurtosis ii. Homogeneity of variance 1. Refers to wanting the variance to be equal for all groups. 2. Want the variances to be similar 3. Do a levine’s test and we want it to be non-significant (<0.05) because that tells us we have a homogeneity of variance 4. Don’t want to see one leptokurtic kurtosis and one platykurtic. iii.Independence of cases (except for the dependent/paired samples t- test 1. Refers to that we don’t want any cluster sampling iv. Interval level data 2 1. Want a DV that’s either interval or ratio 2. Unlike t-test,ANOVAuses an f-test. F-score is linked to a certain p value which will tell you the likelihood of getting your results strictly by chance.
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