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Introduction to Hypothesis Testing: One-Tailed and Two-Tailed Tests

Learn about directional and nondirectional hypotheses, one-tailed and two-tailed tests, cutoff points, and the significance level. Understand how hypothesis tests are reported in research articles.

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Introduction to Hypothesis Testing: One-Tailed and Two-Tailed Tests

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  1. Chapter 4 Introduction to Hypothesis Testing Part 2 Thurs. Sept. 5, 2013

  2. One-Tailed and Two-Tailed Hypothesis Tests • Directional hypotheses – can you make a prediction about the direction of the effect? • One-tailed test – focus on either upper or lower tail of distribution • Ex? • Nondirectional hypotheses – cannot predict a direction of the effect • Two-tailed test – check both tails of the distribution • Ex?

  3. Determining Cutoff Points With Two-Tailed Tests • Divide up the significance between the two tails For 1 tailed-test, if using.05, all .05 is in the relevant tail For 2-tailed test, if using .05, split betw 2 tails, so .05/2, have .025 in each tail

  4. 1- vs. 2-tailed tests • Given that a 1 tailed test has a larger rejection region, • The 1-tailed, directional, test is preferable. • If you have any idea of which direction your results may go, specify that in the Research Hyp. • Leads to better theory testing. • But…another viewpoint:

  5. Notice the change in critical values: • For .05 significance level, • 1-tailed test has 5% of scores in one tail  critical value is 1.64 (or -1.64 if lower tail) • 2-tailed test has 2.5% of scores in each tail  critical values are 1.96 and -1.96 • How does this affect the rejection region? • Two-tailed test example:

  6. Hypothesis Tests in Research Articles • Reported with regard to specific statistical procedures • (r = .78, p < .05) • Look for p < .05 or p < .01 or asterisks in tables (*) to indicate stat significance • “Near significant trend” if p < .10 • Not significant, noted by ‘ns’

  7. Hypothesis Tests in Research Articles • Shown as asterisks in a table of results *Indicates that these results fell in the ‘rejection region’ and they differ significantly from the null hyp. (If no, asterisk  failed to reject the null)

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