NONPARAMETRIC STATISTICS In general, a statistical technique is categorized as NPS if it has at

1. NONPARAMETRIC STATISTICS In general, a statistical technique is categorized as NPS if it has at least one of the following characteristics: • The method is used on nominal data • The method is used in ordinal data • The method is used in interval scale or ratio scale data but there is no assumption regarding the probability distribution of the population where the sample is selected. • Kruskal Wallis Test • Sign Test • Wilcoxon Signed Rank Test • Spearman’s Rank Correlation Test • Mann-Whitney Test

2. Kruskal Wallis Test • An extension of the Mann-Whiteny test or a.k.a Wilcoxon rank sum test of the previous section • It compares more than two independent samples • It is the non-parametric counterpart to the one way analysis of variance • However, unlike one way ANOVA, it does not assume that sample have been drawn from normally distributed populations with equal variances 1. The null hypothesis and alternative hypothesis:

3. 2. Test statistic H • Rank the combined data values if they were from a single group. The smallest data value gets a rank of , the next smallest, 2 and so on. In the event of tie, each of the tied values gets their average rank • Add the rank fro data values from each of the k group, obtaining • The calculate value of the test statistics is:

4. 3.Critical value of H: • The distribution of H is closely approximated by Chi-square distribution whenever each sample size at least 5, for = the level of significance for the test, the critical H is the chi-square value for and the upper tail area is . 4. Rejection region: We will reject 5. Conclusion

5. Example 5.5: Each of three aerospace companies has randomly selected a group of technical staff workers to participate in a training conference sponsored by a supplier firm. The three companies have sent 6, 5 and 7 employees respectively at the beginning of the session. A preliminary test is given, and the scores are shown in the table below. At the 0.05 level, can we conclude that the median scores for the three population of technical staff workers could be the same?

6. Solution: 1.

7. 2. From and we reject 3. Calculated H : 4. Rejection region : 5.

8. Exercise 5.7: Four groups of students were randomly assigned to be taught with four different techniques, and their achievement test scores were recorded. At the 0.05 level, are the distributions of test scores the same, or do they differ in location?

9. Sign Test • The sign test is used to test the null hypothesis and whether or not two groups are equally sized. • In other word, to test of the population proportion for testing in a small sample (usually ) • It based on the direction of the + and – sign of the observation and not their numerical magnitude. • It also called the binomial sign test with the null proportion is 0.5 (Uses the binomial distribution as the decision rule). A binomial experiment consist of nidentical trial with probability of success, pin each trial. The probability of x success in n trials is given by

10. There are two types of sign test : 1. One sample sign test 2. Paired sample sign test

11. One Sample Sign Test Procedure: • Put a + sign for a value greater than the mean value Put a - sign for a value less than the mean value Put a 0 as the value equal to the mean value • Calculate: • The number of + sign, denoted by x • The number of sample, denoted by n (discard/ignore the data with value 0) 3. Run the test i. State the null and alternative hypothesis • Determine level of significance, • Reject • Determining the p – value for the test for n, x and p = 0.5, from binomial probability table base on the type of test being conducted

12. v. Make a decision

13. Example 5.6: The following data constitute a random sample of 15 measurement of the octane rating of a certain kind gasoline: 99.0 102.3 99.8 100.5 99.7 96.2 99.1 102.5 103.3 97.4 100.4 98.9 98.3 98.0 101.6 Test the null hypothesis against the alternative hypothesis at the 0.01 level of significance. Solution: 99.0 102.3 99.8 100.5 99.7 96.2 99.1 102.5 103.3 97.4 100.4 + + + + + - + + + = + 98.9 98.3 98.0 101.6 + + 0 + Number of + sign, x = 12 Number of sample, n = 14 (15 -1) p = 0.5

14. 1. 2. 3. From binomial probability table for x = 12, n = 14 and p = 0.5 4. Since and conclude that the median octane rating of the given kind of gasoline exceeds 98.0

15. Paired Sample Sign Test Procedure: • Calculate the difference, and record the sign of • i. Calculate the number of + sign and denoted as x ii. The number of sample, denoted by n (discard/ignore data with value 0) * probability is 0.5 (p = 0.5) • Run the test i. State the null hypothesis and alternative hypothesis ii. Determine the level of significance iii. Reject iv. Determining the p value for the test for n, x and p = 0.5 from binomial probability table base on type of test being conducted. v. Make decision

16. Example 5.7: 10 engineering students went on a diet program in an attempt to loose weight with the following results: Is the diet program an effective means of losing weight? Do the test at significance level

17. Solution: Let the sign + indicates weight before – weight after > 0 and – indicates weight before – weight after < 0 Thus

18. 1. The + sign indicates the diet program is effective in reducing weight 2. . So we reject 3. Number of + sign, Number of sample, 4. Since . So we can reject and we can conclude that there is sufficient evidence that the diet program is an effective programme to reduce weight.

19. Exercise 5.8: A paint supplier claims that a new additive will reduce the drying time of its acrylic paint. To test his claim, 8 panels of wood are painted with one side of each panel with paint containing the new additive and the other side with paint containing the regular additive. The drying time, in hours, were recorded as follows: Use the sign test at the 0.05 level to test the hypothesis that the new additive have the same drying time as the regular additive.