PSYCH 100A Lecture Notes - Lecture 6: Sampling Distribution, F-Distribution, Null Hypothesis

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28 Mar 2018
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Paired-samples t-test: appropriate for within-group designs with two measurements, outcome variable must be continuous. Difference (change) scores: the paired-samples t test requires two scores per individual (pretest and posttest, hypotheses and computations involve difference scores that subtract the two variables, diff = x2 - x1 = posttest - pretest. If increase from pre --> post then positive. If decrease from pre --> post then negative. Null hypothesis: vast majority of pretest-posttest designs specify a null hypothesis of no change, states that the mean different or change in the full population is zero, h(cid:1004): _diff = (cid:1004) Alternate hypothesis: what kind of effect can we expect to see, requires a two-tailed p-value. One- factor anova: appropriate for research scenarios with a categorical independent variable and one numeric (continuous) dependent variable. Independent-samples t test was used to compare means of two groups: one-factor = one independent variable, anova is appropriate for between-group designs with two or more groups.

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