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Lecture%204 - SOCIOLOGY 005 Lecture 4 Testing Hypotheses...

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Unformatted text preview: SOCIOLOGY 005 Lecture 4 Testing Hypotheses About Two Means Up until this point, we have focused on testing the difference between a sample mean and a population mean identiFed in a null hypothesis We can also test for a difference between two or more sample means Two techniques are available for this kind of bivariate analysis Two-Sample t-test ANOVA Two-Sample t-test Two-sample t-test Can only be used with 2 groups Requires us to know the mean, std. deviation, and N for each t = X 1 ! X 2 s 1 2 N 1 + s 2 2 N 2 Two-Sample t-test In-Class Example Anova Analysis of Variance (ANOVA) is a statistical technique designed to handle situations in which two or more groups are being used to predict the value of a dependent variable It utilizes a F-test to determine if two or more groups have different means The two-sample t-test is a special case of an F-test Anova With ANOVA, we can also calculate: Effects A measure of association Anova Effects Within ANOVA an effect is simply the impact of the classication variable on the dependent variable In order to calculate the effects, we need to know: The grand mean The group mean Anova Effects To calculate effects, we use the following equation: ! K = K " Anova Measure of Association In order to calculate Eta-Squared, our measure of association, it is helpful to wait and calculate this until after we calculate the necessary statistics for our f-test Anova Since ANOVA is related to variability, well be comparing variability between groups and variability within groups This is called between variance and within variance Anova Lets imagine an income distribution in which 3 groups (HS, BA, BA+) had identical means and variances Income In such an example, the within variance of a group would be no different that the within variation of other groups or the...
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Lecture%204 - SOCIOLOGY 005 Lecture 4 Testing Hypotheses...

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