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Teen Growth
Determine whether there is a significant difference in the heights of 15-year-old males and females. |
Physician Referrals 2: Problem |
A study was done to investigate the effect of hospice marketing visits on the change in number of referrals received from doctors. For the two types of visits (one accompanied by a physician, and one by the hospice staff only), the change in referrals after one month (change1) and after three months (change3) were recorded, along with other variables.
Perform the Wilcoxon rank sum test to determine whether the change in referrals after one month differs for the two types of visits. |
SAS Institute Inc.
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Physician Referrals 2: Sample Data | |
The Hospice data set contains data about referrals received from physicians after a visit by a hospice marketing nurse. These are the variables in the data set: Name | Type | Description | | ID | num | physician ID | | Practice | char | type of practice | | Date | char | date of visit | | Change3 | num | change in number of referrals after 3 months | | Change1 | num | change in number of referrals after one month | | Visit | char | type of visit | |
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Source of Data
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This data is sample data from SAS Institute Inc.(database delimiter) |
Physician Referrals 2: Solution |
You’re testing the following hypotheses:
Ho: no difference in change in referrals after
one month between the two types of visits
versus the two-sided alternative
Ha: there is a difference in change in referrals after
one month between the two types of visits
In the results of the Wilcoxon two-sample test for three different tests, the rank sum statistic is S = 378.50. You could choose any of the tests to draw your conclusion. However, in this situation, suppose you want to make your inference based on the exact distribution of the rank sum statistic.
Since your alternative is two-sided, you will rely on the two-sided p-value, which is equal to 0.6531. This does not give sufficient evidence to reject the null hypothesis, so you cannot conclude that there is a difference in the change in referrals after one month between the two types of visits. |
Teen Growth: Problem |
A study compiled the heights and weights of 39 teenagers, all age 15. Use the Wilcoxon rank sum test to determine if there is a significant difference (at level α = 0.05) in the mean heights of 15-year-old males and females. |
Lee Creighton (modified by Paris Faison)
SAS Institute Inc.
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Teen Growth: Sample Data | |
The Htwt15 data set contains the heights and weights of 39 15-year-olds. These are the variables in the data set: Name | Type | Description | | gender | char | gender (male or female) | | height | num | height (in inches) | | weight | num | weight (in pounds) | |
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Source of Data
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Sall, J., Creighton, L., & Lehman, A. (2006). JMP Start Statistics, Third Edition. Cary, NC: SAS Institute Inc. |
Teen Growth: Solution |
The NPAR1WAY procedure in SAS gives the results of two approximations to the Wilcoxon – the Normal and the t approximations (with p-values 0.0002 and 0.0006, respectively) – along with the results of the exact test (p-value = 0.000075). All three of these give strong evidence of a significant difference in the mean heights of 15-year-old males and females (since all p-values are less than α = 0.05). |
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