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

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)