inclass_oct18 - var resp run The first and third screens...

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Stat 296 Fall 2007 The Kruskal-Wallis Test Example: For Example 3.1.1 on page 81, we can apply the Kruskal-Wallis test to the ranks. The data is as follows: Samples from normal populations with μ 1 = 15, μ 2 = 25, μ 3 = 30, σ = 9. Treatment 1 6.08 22.29 7.51 34.36 23.68 Rank 1 1 3 2 13 5 Treatment 2 30.45 22.71 44.52 31.47 36.81 Rank 2 9 4 15 10 14 Treatment 3 32.04 28.03 32.74 23.84 29.64 Rank 3 11 7 12 6 8 Since there are 756,756 possible permutations, the exact Kruskal-Wallis test will take a significant amount of time to run. Instead, we use the MC option which randomly samples 10,000 permutations. data oct18; input treat resp @@; cards; 1 1 1 3 1 2 1 13 1 5 2 9 2 4 2 15 2 10 2 14 3 11 3 7 3 12 3 6 3 8 ; proc npar1way data=oct18 anova scores=data; class treat; exact scores=data /MC; /* The MC option randomly samples the permutations */
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Unformatted text preview: var resp; run; The first and third screens displayed by SAS are as follows. The NPAR1WAY Procedure Analysis of Variance for Variable resp Classified by Variable treat treat N Mean---------------------------------------1 5 4.80 2 5 10.40 3 5 8.80 Source DF Sum of Squares Mean Square F Value Pr > F-------------------------------------------------------------------Among 2 83.20 41.60 2.5366 0.1206 Within 12 196.80 16.40 The NPAR1WAY Procedure Monte Carlo Estimate for the Exact Test Pr >= Chi-Square Estimate 0.1281 99% Lower Conf Limit 0.1195 99% Upper Conf Limit 0.1367 Number of Samples 10000 Initial Seed 725846367 In this case, we find a p-value of 0 . 1281. This is not very significant evidence to reject H ....
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This note was uploaded on 11/20/2011 for the course STATISTICS ST3241 taught by Professor Manwai's during the Spring '11 term at National University of Singapore.

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inclass_oct18 - var resp run The first and third screens...

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