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Chapter 8

Ch. 8 - Hypothesis Testing.docx

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PSYC 2530
Anne Russon

Ch. 8 - Hypothesis Testing Sunday, November 11, 2012 5:55 PM PSYC 2530 Introductory Statistics Chapter 8: Introduction to Hypothesis Testing  Hypothesis testing is an inferential procedure that uses the data from a sample to draw a general conclusion about a population. The procedure begins with a hypothesis about an unknown population. Then a sample is selected, and the sample data provide evidence that either supports or refutes the hypothesis.  There are four steps in the process of hypothesis testing: o 1) State the null hypothesis (H0)  Two hypotheses:  Null hypothesis (H0): Predicts that the independent variable has no effect on the dependent variable for the population  Alternative hypothesis (H1): Predicts that the independent variable does have an effect on the dependent variable o 2) Set the criteria for a decision, locate the critical region  The alpha level, or the level of significance, is a probability value that is used to define the concept of “very unlikely” in a hypothesis test.  The critical region is composed of the extreme sample values that are very unlikely (as defined by the alpha level) to be obtained if the null hypothesis is true. If sample data fall in the critical region, the null hypothesis is rejected.  α = 0.5 (5%), z = ± 1.96  α = 0.01 (1%), z = ± 2.58  α = 0.001 (0.1%), z = ± 3.30 o 3) Collect the data and compute the test statistic  o 4) Make a decision  Two possible outcomes:  1) The sample data are located in the critical region  2) The sample data are not in the critical region and our conclusion is to fail to reject the null hypothesis  A Type I error occurs when a researcher rejects a null hypothesis that is actually true. In a typical research situation, a Type I error means that the researcher concludes that a treatment does have an effect when, in fact, it has no effect.  The alpha level for a hypothesis test is the probability that the test will lead to a Type I error. That is, the alpha level determines the probability of obtaining sample data in the critical region even though the null hypothesis is true. o The probability of a Type I error is equal to the alpha level o The primary concern when selecting an alpha level is to minimize the risk of a Type I error  A Type II error oc
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