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Rank-Based TestsRank-based tests involve comparing the ranks of data rather than specific values to analyze relationships and differences. Examples include the Wilcoxon signed-rank test, Mann-Whitney U test, and Kruskal-Wallis test.
Distribution-free testsDistribution-free tests are used to analyze data without making assumptions about the underlying distribution. Examples include the Sign Test and Runs Test.
Sign TestThe Sign Test is a nonparametric test used to analyze paired data or matched samples to determine if the median difference is zero.
Runs TestThe Runs Test is a nonparametric test used to analyze sequential or time-ordered data to detect departures from randomness or test for trends.
Wilcoxon signed-rank testThe Wilcoxon signed-rank test is a nonparametric test used to determine if the median difference between paired samples is significantly different from zero.
Mann-Whitney U testThe Mann-Whitney U test is a nonparametric test used to compare the distributions of two independent samples.
Kruskal-Wallis testThe Kruskal-Wallis test is a nonparametric test used to compare the distributions of three or more independent samples.
Power and significance levelPower and significance levels are statistical concepts used to evaluate the accuracy and reliability of statistical tests.
Nonparametric RegressionNonparametric regression techniques estimate relationships between variables without assuming a specific functional form.
Resampling MethodsResampling methods, such as bootstrap methods and permutation tests, involve sampling and re-sampling from observed data to make inferences or test hypotheses.
Robust StatisticsRobust statistics provide estimators and techniques that are resistant to outliers and violations of assumptions.

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