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Nonparametric  Hypothesis Testing Guy Lion  December 2005
Nonparametric tests handle variables that are not normally distributed.
When to use these methods   ,[object Object],[object Object],[object Object]
Sign Test  Testing for Differences in  Paired  data. ,[object Object],[object Object],[object Object]
Sign Test Binomial Distribution algorithm
Sign Test testing the creativity of an Ad campaign Classic situation where we need to use a nonparametric test.  This is because the samples are small (17 observations), and the variables are not normally distributed (check Skewness and Kurtosis).
Sign Test testing the creativity of an Ad campaign (continued)
Different view of same data
Mann-Whitney test for  Unpaired  testing Steps. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Note Steps 2 through 6 are similar to the unpaired t Test except it uses  Ranks  instead of  Values .
Example: Testing income of mortg. applicants Testing if applicants for fixed-rate mortgages have higher income than applicants for variable-rate mortgages. The fixed-rate applicants have one high income value ($240,000). Kurtosis and Skewness of both samples confirm they are not normally distributed.  The unpaired t test would not work well.
Sorting and Ranking Ranked in ascending order.  The figures in yellow are identical ($36,500).  They originally ranked 12 th , 13 th , and 14 th .  So, they all received the tied ranking of 13 th .
P Value  (probability difference is due to chance) Based on ranks (not values), there is an 18.3% probability the two samples come from same population.  There is a 81.7% probability that the Variable Rate mortgage applicants have  a higher income  because they have a higher average rank (17.79 vs 13.50).
Mann-Whitney U.  Things to watch for ,[object Object],[object Object],[object Object]
Appendix: The actual Mann-Whitney U Calculation

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Nonparametric Tests Guide

  • 1. Nonparametric Hypothesis Testing Guy Lion December 2005
  • 2. Nonparametric tests handle variables that are not normally distributed.
  • 3.
  • 4.
  • 5. Sign Test Binomial Distribution algorithm
  • 6. Sign Test testing the creativity of an Ad campaign Classic situation where we need to use a nonparametric test. This is because the samples are small (17 observations), and the variables are not normally distributed (check Skewness and Kurtosis).
  • 7. Sign Test testing the creativity of an Ad campaign (continued)
  • 8. Different view of same data
  • 9.
  • 10. Example: Testing income of mortg. applicants Testing if applicants for fixed-rate mortgages have higher income than applicants for variable-rate mortgages. The fixed-rate applicants have one high income value ($240,000). Kurtosis and Skewness of both samples confirm they are not normally distributed. The unpaired t test would not work well.
  • 11. Sorting and Ranking Ranked in ascending order. The figures in yellow are identical ($36,500). They originally ranked 12 th , 13 th , and 14 th . So, they all received the tied ranking of 13 th .
  • 12. P Value (probability difference is due to chance) Based on ranks (not values), there is an 18.3% probability the two samples come from same population. There is a 81.7% probability that the Variable Rate mortgage applicants have a higher income because they have a higher average rank (17.79 vs 13.50).
  • 13.
  • 14. Appendix: The actual Mann-Whitney U Calculation

Notes de l'éditeur

  1. Monday, April 5, 2010