Betweent_Sp08_BBnocolor

Betweent_Sp08_BBnocolor - Introduction Still do not know...

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1 Independent t-test Between-Subjects Design Introduction • Still do not know the population parameters • Dependent t-test: compare two groups of scores from the “same” subjects • Independent t-test: compares two groups of scores from two different groups of subjects – Example: Experimental and control group • Scores are independent of each other Independent t-Test SAMPLE Control Group Experimental Group Differences due to manipulation, not an extraneous variable because mood randomly determined. Introduction Key Focus: Difference between the means of two samples – Comparison distribution = distribution of differences between means
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2 Assumptions 1. Normality 2. Independence of observations 3. Homogeneity of variance Each of the population distributions follows a normal curve The two populations have the same variance Assumptions 3. Homogeneity of Variance (cont’) 3X’s rule SPSS: Levene’s test H 0 : Variances are similar H 1 : Variances are not similar (i.e., violate assumption) p < 0.05 = violation of assumption When to use: Independent t-Test • Interval/ratio data • No information on population parameters (μ, σ ) • Comparing 2 sample means ( M ) • Two groups of different individuals – Usually a control group and a test/experimental group • 1 IV – Only 2 levels
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3 Hypotheses • If the null hypothesis is true, then µ 1 = µ 2 • If the null is true, then the mean of the distribution of differences tells us that µ 1 - µ 2 = 0 • Therefore: H 0 : M 1 - M 2 = 0 H 1 : M 1 - M 2 0 Independent t-Test:
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This note was uploaded on 04/07/2008 for the course PSY 031 taught by Professor Dicorcia during the Spring '08 term at Tufts.

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Betweent_Sp08_BBnocolor - Introduction Still do not know...

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