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Hypothesis Testing

Hypothesis Testing. 2011, 10, 25. Objectives. Review distribution of sample means Descriptive statistics vs. inferential statistics Research hypothesis* Statistical hypothesis testing – One sample z test**. Population For IQ Score. = sample mean; n= 75. Distribution of Sample Means.

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Hypothesis Testing

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  1. Hypothesis Testing 2011, 10, 25

  2. Objectives • Review distribution of sample means • Descriptive statistics vs. inferential statistics • Research hypothesis* • Statistical hypothesis testing – One sample z test**

  3. Population For IQ Score = sample mean; n=75 Distribution of Sample Means Probability Means

  4. Descriptive statistics vs. inferential statistics Descriptive statistics: procedures that help us organize and describe data collected from either a a sample or a population Inferential Statistics: The logic and procedures concerned with making predictions of inferences about the population from observations and analyses of a sample

  5. Research Hypothesis • Law & Order • Not Guilty • Guilty Reject it! Mutually Exclusive Supported

  6. Research Hypothesis (Two-Tailed Test) • The police department of a major city reports that the mean number of auto thefts per neighborhood per year is () 6.88 with a standard deviation () of 1.19. As the mayor of a suburban community just outside the major city, you’re curious as to how the auto theft rate in your community compares. • = 6.88 •   6.88 Reject it! Mutually Exclusive Supported

  7. Research Hypothesis (One-Tailed Test) • Information collected at a local university indicates that students are working on average () 15.2 hours per week while in school with a standard deviation () of 3.5 hours. A research suspects that fraternity members work less than the school average. Information collected from a random sample of 30 fraternity members, reveals a mean of 13.9 hours per week. •   15.2 •  < 15.2 Reject it! Mutually Exclusive Supported

  8. Population For College Students’ Working Hours = sample mean n = 30 Probability

  9. One-Sample z-Test • Step 1: State hypotheses • Step 2: Set your decision criteria • Step 3: Compute mean and Std. Err. • Step 4: Compute the zobs score (test statistic)

  10. One-Sample z-Test • Step 5: Make a decision about your null hypothesis

  11. Lecture Recap: Hypothesis Testing • Review distribution of sample means • Descriptive statistics vs. inferential statistics • Research hypothesis* • Without direction: Two-tailed test • With direction: One-tailed test • One sample z test** • Five steps

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