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Creating Randomization Distributions

This review explains the concept of randomization distributions in hypothesis testing, including how to generate samples and interpret results. Learn where the distribution is centered and what to look for in different scenarios.

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Creating Randomization Distributions

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  1. Section 4.4 Creating Randomization Distributions

  2. Review The p-value of a hypothesis test is 0.02. Using α = 0.05, we • Reject H0 • Do not reject H0 • Reject Ha • Do not reject Ha The p-value is less than α, so we reject H0

  3. Randomization Distribution In a hypothesis test for H0:  = 12 vsHa:  < 12, we have a sample with n = 45 and What do we require about the method to produce randomization samples? •  = 12 •  < 12 We need to generate randomization samples assuming the null hypothesis is true.

  4. Randomization Distribution In a hypothesis test for H0:  = 12 vsHa:  < 12, we have a sample with n = 45 and . Where will the randomization distribution be centered? • 10.2 • 12 • 45 • 1.8 Randomization distributions are always centered around the null hypothesized value.

  5. Randomization Distribution In a hypothesis test for H0:  = 12 vsHa:  < 12, we have a sample with n = 45 and What will we look for on the randomization distribution? • How extreme 10.2 is • How extreme 12 is • How extreme 45 is • What the standard error is • How many randomization samples we collected We want to see how extreme the observed statistic is.

  6. Randomization Distribution In a hypothesis test for H0: 1= 2vsHa: 1> 2, we have a sample with and What do we require about the method to produce randomization samples? • 1 = 2 • 1 > 2 • 26, 21 We need to generate randomization samples assuming the null hypothesis is true.

  7. Randomization Distribution In a hypothesis test for H0: 1= 2vsHa: 1> 2, we have a sample with and Where will the randomization distribution be centered? • 0 • 1 • 21 • 26 • 5 The randomization distribution is centered around the null hypothesized value, 1- 2 = 0

  8. Randomization Distribution In a hypothesis test for H0: 1= 2vsHa: 1> 2, we have a sample with and What do we look for on the randomization distribution? • The standard error • The center point • How extreme 26 is • How extreme 21 is • How extreme 5 is We want to see how extreme the observed difference in means is.

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