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.

Slides:



Advertisements
Similar presentations
Chapter 16 Introduction to Nonparametric Statistics
Advertisements

© 2011 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license.
Introduction to Nonparametric Statistics
McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. Nonparametric Methods Chapter 15.
PSY 307 – Statistics for the Behavioral Sciences Chapter 20 – Tests for Ranked Data, Choosing Statistical Tests.
Ordinal Data. Ordinal Tests Non-parametric tests Non-parametric tests No assumptions about the shape of the distribution No assumptions about the shape.
statistics NONPARAMETRIC TEST
Lecture 10 Non Parametric Testing STAT 3120 Statistical Methods I.
Copyright © 2010, 2007, 2004 Pearson Education, Inc Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
© 2003 Pearson Prentice Hall Statistics for Business and Economics Nonparametric Statistics Chapter 14.
Chapter 12 Chi-Square Tests and Nonparametric Tests
Chapter 14 Analysis of Categorical Data
Chapter 12 Chi-Square Tests and Nonparametric Tests
© 2002 Prentice-Hall, Inc.Chap 8-1 Statistics for Managers using Microsoft Excel 3 rd Edition Chapter 8 Two Sample Tests with Numerical Data.
Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 8-1 Business Statistics: A Decision-Making Approach 6 th Edition Chapter.
Wilcoxon Tests What is the Purpose of Wilcoxon Tests? What are the Assumptions? How does the Wilcoxon Rank-Sum Test Work? How does the Wilcoxon Matched-
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc. Chap 9-1 Chapter 9 Fundamentals of Hypothesis Testing: One-Sample Tests Basic Business Statistics.
Statistics for Managers Using Microsoft® Excel 5th Edition
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Statistics for Business and Economics 7 th Edition Chapter 9 Hypothesis Testing: Single.
© 2004 Prentice-Hall, Inc.Chap 10-1 Basic Business Statistics (9 th Edition) Chapter 10 Two-Sample Tests with Numerical Data.
Basic Business Statistics (9th Edition)
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 12 Chi-Square Tests and Nonparametric Tests
Chapter 15 Nonparametric Statistics
AM Recitation 2/10/11.
Statistics for Managers Using Microsoft Excel, 5e © 2008 Prentice-Hall, Inc.Chap 12-1 Statistics for Managers Using Microsoft® Excel 5th Edition Chapter.
Chapter 10 Hypothesis Testing
Chapter 14: Nonparametric Statistics
Business Statistics, A First Course (4e) © 2006 Prentice-Hall, Inc. Chap 9-1 Chapter 9 Fundamentals of Hypothesis Testing: One-Sample Tests Business Statistics,
NONPARAMETRIC STATISTICS
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
Chapter 9 Hypothesis Testing: Single Population
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
© 2002 Prentice-Hall, Inc.Chap 9-1 Statistics for Managers Using Microsoft Excel 3 rd Edition Chapter 9 Analysis of Variance.
CHAPTER 14: Nonparametric Methods
Lesson Inferences about the Differences between Two Medians: Dependent Samples.
CHAPTER 14: Nonparametric Methods to accompany Introduction to Business Statistics seventh edition, by Ronald M. Weiers Presentation by Priscilla Chaffe-Stengel.
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 11-1 Chapter 11 Chi-Square Tests and Nonparametric Tests Statistics for.
© 2000 Prentice-Hall, Inc. Statistics Nonparametric Statistics Chapter 14.
A Course In Business Statistics 4th © 2006 Prentice-Hall, Inc. Chap 9-1 A Course In Business Statistics 4 th Edition Chapter 9 Estimation and Hypothesis.
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.
MGT-491 QUANTITATIVE ANALYSIS AND RESEARCH FOR MANAGEMENT OSMAN BIN SAIF Session 26.
1 Nonparametric Statistical Techniques Chapter 17.
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 8-1 Chapter 8 Fundamentals of Hypothesis Testing: One-Sample Tests Statistics.
Chap 8-1 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. A Course In Business Statistics 4 th Edition Chapter 8 Introduction to Hypothesis.
Lesson 15 - R Chapter 15 Review. Objectives Summarize the chapter Define the vocabulary used Complete all objectives Successfully answer any of the review.
Copyright ©2011 Pearson Education, Inc. publishing as Prentice Hall 12-1 Chapter 12 Chi-Square Tests and Nonparametric Tests Statistics for Managers using.
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.
Ka-fu Wong © 2003 Chap Dr. Ka-fu Wong ECON1003 Analysis of Economic Data.
Statistics in Applied Science and Technology Chapter14. Nonparametric Methods.
NON-PARAMETRIC STATISTICS
Biostatistics Nonparametric Statistics Class 8 March 14, 2000.
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
Chapter Fifteen Chi-Square and Other Nonparametric Procedures.
Copyright © 2010, 2007, 2004 Pearson Education, Inc Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
Lesson Test to See if Samples Come From Same Population.
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Statistics for Business and Economics 8 th Edition Chapter 9 Hypothesis Testing: Single.
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.
Non-parametric Tests Research II MSW PT Class 8. Key Terms Power of a test refers to the probability of rejecting a false null hypothesis (or detect a.
Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc. CHAPTER 14: Nonparametric Methods to accompany Introduction to Business Statistics fifth.
Chapter 12 Chi-Square Tests and Nonparametric Tests
Lecture Slides Elementary Statistics Twelfth Edition
Nonparametric Statistics
Presentation transcript:

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 to Nonparametric Statistics

CD-ROM Chap 16-2 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Chapter Goals After completing this chapter, you should be able to:  Recognize when and how to use the Wilcoxon signed rank test for a population median  Recognize the situations for which the Wilcoxon signed rank test applies and be able to use it for decision-making  Know when and how to perform a Mann-Whitney U-test  Perform nonparametric analysis of variance using the Kruskal-Wallis one-way ANOVA

CD-ROM Chap 16-3 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Nonparametric Statistics Fewer restrictive assumptions about data levels and underlying probability distributions Population distributions may be skewed The level of data measurement may only be ordinal or nominal

CD-ROM Chap 16-4 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Wilcoxon Signed Rank Test Used to test a hypothesis about one population median the median is the midpoint of the distribution: 50% below, 50% above A hypothesized median is rejected if sample results vary too much from expectations no highly restrictive assumptions about the shape of the population distribution are needed

CD-ROM Chap 16-5 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. The W Test Statistic Performing the Wilcoxon Signed Rank Test Calculate the test statistic W using these steps: Step 1: collect sample data Step 2: compute d i = difference between each value and the hypothesized median Step 3: convert d i values to absolute differences

CD-ROM Chap 16-6 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. The W Test Statistic Performing the Wilcoxon Signed Rank Test Step 4: determine the ranks for each d i value eliminate zero d i values Lowest d i value = 1 For ties, assign each the average rank of the tied observations (continued)

CD-ROM Chap 16-7 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. The W Test Statistic Performing the Wilcoxon Signed Rank Test Step 5: Create R+ and R- columns for data values greater than the hypothesized median, put the rank in an R+ column for data values less than the hypothesized median, put the rank in an R- column (continued)

CD-ROM Chap 16-8 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. The W Test Statistic Performing the Wilcoxon Signed Rank Test Step 6: the test statistic W is the sum of the ranks in the R+ column Test the hypothesis by comparing the calculated W to the critical value from the table in appendix P Note that n = the number of non-zero d i values (continued)

CD-ROM Chap 16-9 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Example The median class size is claimed to be 40 Sample data for 8 classes is randomly obtained Compare each value to the hypothesized median to find difference Class size = x i Difference d i = x i – 40 | d i |

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Example Rank the absolute differences: | d i |Rank tied (continued)

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Example Put ranks in R+ and R- columns and find sums: Class size = x i Difference d i = x i – 40 | d i |RankR+R  = 27  = 9 (continued) These three are below the claimed median, the others are above

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Completing the Test H 0 : Median = 40 H A : Median ≠ 40 Test at the  =.05 level: This is a two-tailed test and n = 8, so find W L and W U in appendix P: W L = 3 and W U = 33 The calculated test statistic is W =  R+ = 27

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Completing the Test H 0 : Median = 40 H A : Median ≠ 40 W L = 3 and W U = 33 W L < W < W U so do not reject H 0 (there is not sufficient evidence to conclude that the median class size is different than 40) (continued) W L = 3 do not reject H 0 reject H 0 W =  R+ = 27 W U = 33 reject H 0

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. If the Sample Size is Large The W test statistic approaches a normal distribution as n increases For n > 20, W can be approximated by where W = sum of the R+ ranks d = number of non-zero d i values

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Nonparametric Tests for Two Population Centers Nonparametric Tests for Two Population Centers Wilcoxon Matched-Pairs Signed Rank Test Mann-Whitney U-test Large Samples Small Samples Large Samples Small Samples

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Mann-Whitney U-Test Used to compare two samples from two populations Assumptions: The two samples are independent and random The value measured is a continuous variable The measurement scale used is at least ordinal If they differ, the distributions of the two populations will differ only with respect to the central location

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Consider two samples combine into a singe list, but keep track of which sample each value came from rank the values in the combined list from low to high For ties, assign each the average rank of the tied values separate back into two samples, each value keeping its assigned ranking sum the rankings for each sample Mann-Whitney U-Test (continued)

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. If the sum of rankings from one sample differs enough from the sum of rankings from the other sample, we conclude there is a difference in the population medians Mann-Whitney U-Test (continued)

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. (continued) Mann-Whitney U-Test Mann-Whitney U-Statistics where: n 1 and n 2 are the two sample sizes  R 1 and  R 2 = sum of ranks for samples 1 and 2

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. (continued) Mann-Whitney U-Test Claim: Median class size for Math is larger than the median class size for English A random sample of 9 Math and 9 English classes is selected (samples do not have to be of equal size) Rank the combined values and then split them back into the separate samples

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Suppose the results are: Class size (Math, M)Class size (English, E) (continued) Mann-Whitney U-Test

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. SizeRank SizeRank Ranking for combined samples tied (continued) Mann-Whitney U-Test

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Split back into the original samples: Class size (Math, M) Rank Class size (English, E) Rank  = 104  = 67 (continued) Mann-Whitney U-Test

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. H 0 : Median M ≤ Median E H A : Median M > Median E Claim: Median class size for Math is larger than the median class size for English Note: U 1 + U 2 = n 1 n 2 (continued) Mann-Whitney U-Test Math: English:

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. The Mann-Whitney U tables in Appendices L and M give the lower tail of the U-distribution For one-tailed tests like this one, check the alternative hypothesis to see if U 1 or U 2 should be used as the test statistic Since the alternative hypothesis indicates that population 1 (Math) has a higher median, use U 1 as the test statistic (continued) Mann-Whitney U-Test

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Use U 1 as the test statistic: U = 22 Compare U = 22 to the critical value U  from the appropriate table For sample sizes less than 9, use Appendix L For samples sizes from 9 to 20, use Appendix M If U < U , reject H 0 (continued) Mann-Whitney U-Test

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Since U  U , do not reject H 0 Use U 1 as the test statistic: U = 19 U  from Appendix M for  =.05, n 1 = 9 and n 2 = 9 is U  = 7 (continued) Mann-Whitney U-Test U  = 7 U = 19 do not reject H 0 reject H 0

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Mann-Whitney U-Test for Large Samples The table in Appendix M includes U  values only for sample sizes between 9 and 20 The U statistic approaches a normal distribution as sample sizes increase If samples are larger than 20, a normal approximation can be used

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Mann-Whitney U-Test for Large Samples The mean and standard deviation for Mann-Whitney U Test Statistic: (continued) Where n 1 and n 2 are sample sizes from populations 1 and 2

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Mann-Whitney U-Test for Large Samples Normal approximation for Mann-Whitney U Test Statistic: (continued)

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Large Sample Example We wish to test Suppose two samples are obtained: n 1 = 40, n 2 = 50 When rankings are completed, the sum of ranks for sample 1 is  R 1 = 1475 When rankings are completed, the sum of ranks for sample 2 is  R 2 = 2620 H 0 : Median 1  Median 2 H A : Median 1 < Median 2

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. U statistic is found to be U = 655 Since the alternative hypothesis indicates that population 2 has a higher median, use U 2 as the test statistic Compute the U statistics: Large Sample Example (continued)

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Since z = < , we reject H 0 Reject H 0  =.05 Do not reject H 0 0 Large Sample Example (continued)

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Wilcoxon Matched-Pairs Signed Rank Test The Mann-Whitney U-Test is used when samples from two populations are independent If samples are paired, they are not independent Use Wilcoxon Matched-Pairs Signed Rank Test with paired samples

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. The Wilcoxon T Test Statistic Performing the Small-Sample Wilcoxon Matched Pairs Test (for n < 25) Calculate the test statistic T using these steps: Step 1: collect sample data Step 2: compute d i = difference between the sample 1 value and its paired sample 2 value Step 3: rank the differences, and give each rank the same sign as the sign of the difference value

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. The Wilcoxon T Test Statistic Performing the Small-Sample Wilcoxon Matched Pairs Test (for n < 25) Step 4: The test statistic is the sum of the absolute values of the ranks for the group with the smaller expected sum Look at the alternative hypothesis to determine the group with the smaller expected sum For two tailed tests, just choose the smaller sum (continued)

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Small Sample Example Paired samples, n = 9: Value (before)Value (after) Claim: Median value is smaller after than before

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Small Sample Example Paired samples, n = 9: Value (before) Value (after) Difference d Rank of d Ranks with smaller expected sum  = T = 13 (continued)

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. The calculated T value is T = 13 Complete the test by comparing the calculated T value to the critical T-value from Appendix N For n = 9 and  =.025 for a one-tailed test, T  = 6 Since T  T , do not reject H 0 T  = 6 T = 13 do not reject H 0 reject H 0 Small Sample Example (continued)

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Wilcoxon Matched Pairs Test for Large Samples The table in Appendix N includes T  values only for sample sizes from 6 to 25 The T statistic approaches a normal distribution as sample size increases If the number of paired values is larger than 25, a normal approximation can be used

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. The mean and standard deviation for Wilcoxon T : (continued) where n is the number of paired values Wilcoxon Matched Pairs Test for Large Samples

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Mann-Whitney U-Test for Large Samples Normal approximation for the Wilcoxon T Test Statistic: (continued)

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Tests the equality of more than 2 population medians Assumptions: variables have a continuous distribution. the data are at least ordinal. samples are independent. samples come from populations whose only possible difference is that at least one may have a different central location than the others. Kruskal-Wallis One-Way ANOVA

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Kruskal-Wallis Test Procedure Obtain relative rankings for each value In event of tie, each of the tied values gets the average rank Sum the rankings for data from each of the k groups Compute the H test statistic

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Kruskal-Wallis Test Procedure The Kruskal-Wallis H test statistic: (with k – 1 degrees of freedom) where: N = Sum of sample sizes in all samples k = Number of samples R i = Sum of ranks in the i th sample n i = Size of the i th sample (continued)

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Complete the test by comparing the calculated H value to a critical  2 value from the chi-square distribution with k – 1 degrees of freedom (The chi-square distribution is Appendix G) Decision rule Reject H 0 if test statistic H >  2  Otherwise do not reject H 0 (continued) Kruskal-Wallis Test Procedure

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Do different departments have different class sizes? Kruskal-Wallis Example Class size (Math, M) Class size (English, E) Class size (History, H)

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Do different departments have different class sizes? Kruskal-Wallis Example Class size (Math, M) Ranking Class size (English, E) Ranking Class size (History, H) Ranking  = 44  = 56  = 20

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. The H statistic is (continued) Kruskal-Wallis Example

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Since H = 6.72 < do not reject H 0 (continued) Kruskal-Wallis Example Compare H = 6.72 to the critical value from the chi-square distribution for 5 – 1 = 4 degrees of freedom and  =.05: There is not sufficient evidence to reject that the population medians are all equal

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Kruskal-Wallis Correction If tied rankings occur, give each observation the mean rank for which it is tied The H statistic is influenced by ties, and should be corrected Correction for tied rankings: where: g = Number of different groups of ties t i = Number of tied observations in the i th tied group of scores N = Total number of observations

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. H Statistic Corrected for Tied Rankings Corrected H statistic:

CD-ROM Chap A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. Chapter Summary Developed and applied the Wilcoxon signed rank W-test for a population median Small Samples Large sample z approximation Developed and applied the Mann-Whitney U-test for two population medians Small Samples Large Sample z approximation Used the Wilcoxon Matched-Pairs T-test for paired samples Small Samples Large sample z approximation Applied the Kruskal-Wallis H-test for multiple population medians