NONPARAMETRIC STATISTICS In general, a statistical technique is categorized as NPS if it has at least one of the following characteristics: 1. The method.

Slides:



Advertisements
Similar presentations
Prepared by Lloyd R. Jaisingh
Advertisements

Elementary Statistics
The Kruskal-Wallis H Test
1 Chapter 20: Statistical Tests for Ordinal Data.
Chapter 16 Introduction to Nonparametric Statistics
Introduction to Nonparametric Statistics
EPI 809 / Spring 2008 Chapter 9 Nonparametric Statistics.
statistics NONPARAMETRIC TEST
NONPARAMETRIC STATISTICS
© 2003 Pearson Prentice Hall Statistics for Business and Economics Nonparametric Statistics Chapter 14.
Chapter 14 Analysis of Categorical Data
Statistics 07 Nonparametric Hypothesis Testing. Parametric testing such as Z test, t test and F test is suitable for the test of range variables or ratio.
1 Pertemuan 11 Analisis Varians Data Nonparametrik Matakuliah: A0392 – Statistik Ekonomi Tahun: 2006.
The Kruskal-Wallis Test The Kruskal-Wallis test is a nonparametric test that can be used to determine whether three or more independent samples were.
Chapter 15 Nonparametric Statistics
ABOUT TWO DEPENDENT POPULATIONS
Nonparametric or Distribution-free Tests
Statistical Inference for Two Samples
AM Recitation 2/10/11.
Chapter 11 Nonparametric Tests Larson/Farber 4th ed.
11 Chapter Nonparametric Tests © 2012 Pearson Education, Inc.
Hypothesis Testing Charity I. Mulig. Variable A variable is any property or quantity that can take on different values. Variables may take on discrete.
NONPARAMETRIC STATISTICS
14 Elements of Nonparametric Statistics
NONPARAMETRIC STATISTICS
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
Copyright © Cengage Learning. All rights reserved. 14 Elements of Nonparametric Statistics.
CHAPTER 14: Nonparametric Methods
Chapter 11 Nonparametric Tests.
What are Nonparametric Statistics? In all of the preceding chapters we have focused on testing and estimating parameters associated with distributions.
CHAPTER 14: Nonparametric Methods to accompany Introduction to Business Statistics seventh edition, by Ronald M. Weiers Presentation by Priscilla Chaffe-Stengel.
© 2000 Prentice-Hall, Inc. Statistics Nonparametric Statistics Chapter 14.
1/23 Ch10 Nonparametric Tests. 2/23 Outline Introduction The sign test Rank-sum tests Tests of randomness The Kolmogorov-Smirnov and Anderson- Darling.
1 1 Slide © 2003 South-Western/Thomson Learning™ Slides Prepared by JOHN S. LOUCKS St. Edward’s University.
Biostatistics, statistical software VII. Non-parametric tests: Wilcoxon’s signed rank test, Mann-Whitney U-test, Kruskal- Wallis test, Spearman’ rank correlation.
Ordinally Scale Variables
Copyright © Cengage Learning. All rights reserved. 14 Elements of Nonparametric Statistics.
Nonparametric Statistics. In previous testing, we assumed that our samples were drawn from normally distributed populations. This chapter introduces some.
1 Nonparametric Statistical Techniques Chapter 17.
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 11-1 Chapter 11 Chi-Square Tests and Nonparametric Tests Statistics for.
©The McGraw-Hill Companies, Inc. 2008McGraw-Hill/Irwin Non-parametric: Analysis of Ranked Data Chapter 18.
Kruskal-Wallis H TestThe Kruskal-Wallis H Test is a nonparametric procedure that can be used to compare more than two populations in a completely randomized.
CHAPTER 5 NONPARAMETRIC STATISTICS In general, a statistical technique is categorized as NPS if it has at least one of the following characteristics: 1.
NONPARAMETRIC STATISTICS In general, a statistical technique is categorized as NPS if it has at least one of the following characteristics: 1. The method.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
CD-ROM Chap 16-1 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. A Course In Business Statistics 4 th Edition CD-ROM Chapter 16 Introduction.
NONPARAMETRIC STATISTICS In general, a statistical technique is categorized as NPS if it has at least one of the following characteristics: 1. The method.
NON-PARAMETRIC STATISTICS
Inferences Concerning Variances
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Nonparametric Statistics.
Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Nonparametric Statistics.
1 QNT 531 Advanced Problems in Statistics and Research Methods WORKSHOP 5 By Dr. Serhat Eren University OF PHOENIX.
Lesson Test to See if Samples Come From Same Population.
SUMMARY EQT 271 MADAM SITI AISYAH ZAKARIA SEMESTER /2015.
Nonparametric statistics. Four levels of measurement Nominal Ordinal Interval Ratio  Nominal: the lowest level  Ordinal  Interval  Ratio: the highest.
1 Nonparametric Statistical Techniques Chapter 18.
Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc. CHAPTER 14: Nonparametric Methods to accompany Introduction to Business Statistics fifth.
McGraw-Hill/Irwin © 2003 The McGraw-Hill Companies, Inc.,All Rights Reserved. Part Four ANALYSIS AND PRESENTATION OF DATA.
Nonparametric Statistics
NONPARAMETRIC STATISTICS
Chapter 12 Chi-Square Tests and Nonparametric Tests
NONPARAMETRIC STATISTICS
Part Four ANALYSIS AND PRESENTATION OF DATA
CHAPTER 12 ANALYSIS OF VARIANCE
Data Analysis and Interpretation
The Rank-Sum Test Section 15.2.
NONPARAMETRIC METHODS
Nonparametric Statistics
Presentation transcript:

NONPARAMETRIC STATISTICS In general, a statistical technique is categorized as NPS if it has at least one of the following characteristics: 1. The method is used on nominal data 2. The method is used in ordinal data 3. 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

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:

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:

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

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? Test score Firm 1Firm 2Firm

Solution: 1. Test score Firm 1RankFirm 2RankFirm 3Rank

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

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?

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 n identical trial with probability of success, p in each trial. The probability of x success in n trials is given by

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

One Sample Sign Test Procedure: 1. 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 2. Calculate: i.The number of + sign, denoted by x ii.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 ii.Determine 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 the type of test being conducted

v.Make a decision Sign of p - value Two tail test= Right tail test> Left tail test<

Example 5.6: The following data constitute a random sample of 15 measurement of the octane rating of a certain kind gasoline: Test the null hypothesis against the alternative hypothesis at the 0.01 level of significance. Solution: = Number of + sign, x = 12 Number of sample, n = 14 (15 -1) p = 0.5

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

Paired Sample Sign Test Procedure: 1. Calculate the difference, and record the sign of 2. 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 ) 3. 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 Sign of p - value Two tail test= Right tail test> Left tail test<

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 NameWeight beforeWeight after Abu6958 Ah Lek8273 Sami7670 Kassim8971 Chong9382 Raja7966 Busu7275 Wong6871 Ali8367 Tan10373

Solution: Let the sign + indicates weight before – weight after > 0 and – indicates weight before – weight after < 0 Thus NameWeight beforeWeight after Sign Abu Ah Lek Sami Kassim Chong Raja Busu Wong Ali Tan

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.

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. PanelDrying Times New AdditiveRegular Additive