NonParametric (Fields Ch. 15) Flashcards
Kolmogorov-Smirnov Z
not to be confused with the Kolmogorov-Smirnov test that tests whether a sample comes from a normally distributed population. This tests whether two groups have been drawn from the same population (regardless of what that population may be). It does much the same as the Mann-Whitney test and Wilcoxon rank-sum test! This test tends to have better power than the Mann-Whitney test when sample sizes are less than about 25 per group.
Monte Carlo method
a term applied to the process of using data simulations to solve statistical problems. Its name comes from the use of Monte Carlo roulette tables to generate ‘random’ numbers in the pre-computer age.
Non-parametric tests
a family of statistical procedures that do not rely on the restrictive assumptions of parametric tests. In particular, they do not assume that the sampling distribution is normally distributed.
Wilcoxon signed-rank test
a non-parametric test that looks for differences between two related samples. It is the non-parametric equivalent of the related t-test.
nonparametric statistics
In statistics, the term “nonparametric statistics” refers to comparative properties (statistics) of the data, or population, which do not include the typical parameters of mean, variance, standard deviation, etc. Unlike parametric statistics, nonparametric statistics make no assumptions about the probability distributions of the variables being assessed
Covariance
The relationship that occurs as one variable begins to deviate from the mean with another variable.
+ variance means as one variable deviates from the mean so does the other.
This is a crude member of the relationship. When standardized you get Pearson correlation coefficient ®
The 4 most common non-parametric procedures:
- Mann-Whitney test
- Wilcoxon signed-rank test
- Friedman’s test
- Kruskal-Wallis test
