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Wilcoxon’s Rank-Sum Test (two independent samples) n1 + n2 ≤ 25: Same Distributions

Wilcoxon’s Rank-Sum Test (two independent samples) n1 + n2 ≤ 25: Same Distributions. Wilcoxon’s Rank-Sum Test (two independent samples) n1 + n2 ≤ 25: Different Distributions. Wilcoxon’s Rank-Sum Test (two independent samples) n1 + n2 > 25: Different Distributions.

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Wilcoxon’s Rank-Sum Test (two independent samples) n1 + n2 ≤ 25: Same Distributions

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  1. Wilcoxon’s Rank-Sum Test (two independent samples) n1 + n2 ≤ 25: Same Distributions

  2. Wilcoxon’s Rank-Sum Test (two independent samples) n1 + n2 ≤ 25: Different Distributions

  3. Wilcoxon’s Rank-Sum Test (two independent samples) n1 + n2 > 25: Different Distributions

  4. Wilcoxon’s Matched Pairs Signed Ranks Test (for paired scores) n ≤ 50

  5. Wilcoxon’s Matched Pairs Signed Ranks Test (for paired scores) n > 50 • Randomly split the Adult data set at 50% 100 times. • For each training/testing data set, run Naïve Bayes and J48 and record their accuracy values as a pair for which we compute the difference in accuracy • Determine the signed ranks of the difference for each pair (as previous example – data is omitted due to space constraints) • We get W+ = 0 and W- = 5050 (J48 produces higher accuracy always), N = 100 • We get, mean(W) = 2525, STD(W)=290.84 • Z=(0-2525)/290.84 = -8.6818 < 1.96 (at alpha = 0.05)

  6. What is the Effect Size? (The effect of using LaPlace smoothing on accuracy of J48)

  7. One-Way ANOVA (J48 on three domains)

  8. One-Way ANOVA (J48 on three domains)

  9. Two-Way ANOVA (J48 & N.B. on 3 domains)

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