lecture 11 Hypothesis Testing(pt.1)

# lecture 11 Hypothesis Testing(pt.1) - Hypothesis Testing...

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Unformatted text preview: Hypothesis Testing • Assuming that a given hypothesis were true: • 1) What are the characteristics (e.g., shape, mean, variance) of the sampling distribution speciFed by that hypothesis? • 2) On the basis of that hypothetical sampling distribution, what would be considered a rare, as opposed to a common outcome; i.e., what sort of outcome would lead us to doubt that the hypothesis was true? 1 Common vs. Rare Outcomes • Rare outcomes are those which fall in the tails of the hypothetical sampling distribution • Common outcomes are those which fall in the center of the hypothetical sampling distribution • “Statistically signiFcant” 2 A Revised Anatomy of a Hypothesis Test • Step #1: State the statistical hypotheses • Step #2: Specify the sample size and sampling distribution • Step #3: Specify the decision rule • Step #4: Specify the test statistic • Step #5: Carry out calculations • Step #6: Interpret Results 3 Statistical Hypotheses • Two components: • Null Hypothesis ( H ) • Usually the hypothesis that there is no effect • The hypothesis that we seek to falsify • Alternative Hypothesis ( H 1 ) • SpeciFes the basic effect that the researcher is expecting to observe • Not directly tested 4 One vs. Two-Tailed Hypotheses • Two-Tailed (Nondirectional) Tests • The expectation ( H 1 ) is simply that a difference will be observed • One-Tailed (Directional) Tests • The expectation (...
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## This note was uploaded on 01/21/2009 for the course PSYC 60 taught by Professor Ard during the Winter '08 term at UCSD.

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lecture 11 Hypothesis Testing(pt.1) - Hypothesis Testing...

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