This preview shows pages 1–6. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
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. TwoTailed Hypotheses TwoTailed (Nondirectional) Tests The expectation ( H 1 ) is simply that a difference will be observed OneTailed (Directional) Tests The expectation (...
View Full
Document
 Winter '08
 Ard

Click to edit the document details