1. Section 13.1-1 Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series by Mario F. Triola

2. Section 13.1-2 Copyright © 2014, 2012, 2010 Pearson Education, Inc. Chapter 13 Nonparametric Statistics 13-1Review and Preview 13-2Sign Test 13-3Wilcoxon Signed-Ranks Test for Matched Pairs 13-4Wilcoxon Rank-Sum Test for Two Independent Samples 13-5Kruskal-Wallis Test 13-6Rank Correction 13-7Runs Test for Randomness

3. Section 13.1-3 Copyright © 2014, 2012, 2010 Pearson Education, Inc. In the preceding chapters, we presented a variety of different methods of inferential statistics. Many of those methods require normally distributed populations and are based on sampling from a population with specific parameters, such as the mean μ, standard deviation σ, or population proportion p. Review

4. Section 13.1-4 Copyright © 2014, 2012, 2010 Pearson Education, Inc. Definitions Parametric tests have requirements about the nature or shape of the populations involved. Nonparametric tests do not require that samples come from populations with normal distributions or have any other particular distributions. Consequently, nonparametric tests are called distribution-free tests. Preview

5. Section 13.1-5 Copyright © 2014, 2012, 2010 Pearson Education, Inc. Advantages of Nonparametric Methods 1. Nonparametric methods can be applied to a wide variety of situations because they do not have the more rigid requirements of the corresponding parametric methods. In particular, nonparametric methods do not require normally distributed populations. 2. Unlike parametric methods, nonparametric methods can often be applied to categorical data, such as the genders of survey respondents.

6. Section 13.1-6 Copyright © 2014, 2012, 2010 Pearson Education, Inc. Disadvantages of Nonparametric Methods 1. Nonparametric methods tend to waste information because exact numerical data are often reduced to a qualitative form. 2. Nonparametric tests are not as efficient as parametric tests, so with a nonparametric test we generally need stronger evidence (such as a larger sample or greater differences) in order to reject a null hypothesis.

7. Section 13.1-7 Copyright © 2014, 2012, 2010 Pearson Education, Inc. Efficiency of Nonparametric Methods Example: All things being equal, nonparametric rank correlation requires 100 sample observations to achieve the same results as 91 sample observations analyzed through parametric linear correlation, assuming the stricter requirements for using the parametric test are met.

8. Section 13.1-8 Copyright © 2014, 2012, 2010 Pearson Education, Inc. Definitions Data are sorted when they are arranged according to some criterion, such as smallest to the largest or best to worst. A rank is a number assigned to an individual sample item according to its order in the sorted list. The first item is assigned a rank of 1, the second is assigned a rank of 2, and so on.

9. Section 13.1-9 Copyright © 2014, 2012, 2010 Pearson Education, Inc. Handling Ties in Ranks Find the mean of the ranks involved and assign this mean rank to each of the tied items.