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|Rank-Based Tests||Rank-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 tests||Distribution-free tests are used to analyze data without making assumptions about the underlying distribution. Examples include the Sign Test and Runs Test.|
|Sign Test||The Sign Test is a nonparametric test used to analyze paired data or matched samples to determine if the median difference is zero.|
|Runs Test||The 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 test||The 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 test||The Mann-Whitney U test is a nonparametric test used to compare the distributions of two independent samples.|
|Kruskal-Wallis test||The Kruskal-Wallis test is a nonparametric test used to compare the distributions of three or more independent samples.|
|Power and significance level||Power and significance levels are statistical concepts used to evaluate the accuracy and reliability of statistical tests.|
|Nonparametric Regression||Nonparametric regression techniques estimate relationships between variables without assuming a specific functional form.|
|Resampling Methods||Resampling methods, such as bootstrap methods and permutation tests, involve sampling and re-sampling from observed data to make inferences or test hypotheses.|
|Robust Statistics||Robust statistics provide estimators and techniques that are resistant to outliers and violations of assumptions.|