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Creating Randomization Distributions

Section 4.4. Creating Randomization Distributions. Review. The p-value of a hypothesis test is 0.02. Using α = 0.05, we. Reject H 0 Do not reject H 0 Reject H a Do not reject H a. The p-value is less than α , so we reject H 0. Randomization Distribution.

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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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