{"id":147,"date":"2018-03-09T00:13:00","date_gmt":"2018-03-08T23:13:00","guid":{"rendered":"https:\/\/kindsonthegenius.com\/blog\/2018\/03\/09\/what-are-non-parametric-tests\/"},"modified":"2020-08-22T20:26:09","modified_gmt":"2020-08-22T18:26:09","slug":"what-are-non-parametric-tests","status":"publish","type":"post","link":"https:\/\/kindsonthegenius.com\/blog\/what-are-non-parametric-tests\/","title":{"rendered":"What are Non-Parametric Tests in Statistics?"},"content":{"rendered":"<p>Non-parametric tests which are also called distribution-free tests are applied when the distribution of the population is not known. In other words, non-parametric tests makes no assumption about the probability distributions of the observations.<\/p>\n<p>See also <a href=\"http:\/\/kindsonthegenius.blogspot.com\/2018\/03\/parametric-tests-in-statistics-when-to.html\" target=\"_blank\" rel=\"noopener\">What are Parametric Tests<\/a><br \/>\n<span style=\"color: #990000;\"><span style=\"font-size: large;\"><br \/>\n<\/span><\/span><\/p>\n<div style=\"text-align: center;\"><span style=\"color: #990000;\"><span style=\"font-size: large;\"><b>Common non-Parametric Tests<\/b><\/span><\/span><\/div>\n<p><b><a href=\"http:\/\/kindsonthegenius.blogspot.com\/2018\/03\/kolmogorov-smirnov-goodness-of-fit-test.html\" target=\"_blank\" rel=\"noopener\">Kolmogorov-Smirnov Test<\/a>:<\/b> This test is used to examine wether a sample is taken from a given distribution. In case of two samples, it tests if the two samples are taken from the same distribution.<\/p>\n<p><a href=\"http:\/\/kindsonthegenius.blogspot.com\/2018\/06\/how-to-perform-mann-witney-u-test.html\" target=\"_blank\" rel=\"noopener\"><b>Mann-Withney U<\/b><\/a> (also called Wilcoxon rank sum test): Just like the Kolmogorov-Smirnov test, this is used to test\u00a0 wether two samples are drawn from the same distribution.<\/p>\n<p><a href=\"http:\/\/kindsonthegenius.blogspot.com\/2018\/03\/hypothesis-testing-problems-question-9.html\" target=\"_blank\" rel=\"noopener\"><b>Wilcoxon signed-rank test<\/b>:<\/a> This is used to test wether matched pair samples are drawn from populations with different mean ranks.<\/p>\n<p><b>Sign Test<\/b>: Used to test whether matched pair samples are taken from populations with equal medians.<\/p>\n<p><b>Kruskal-Wallis<\/b> one-way ANOVA on ranks test: This is used to test if two samples are taken from the same distribution. It compares two samples which could be of equal or different sample sizes.<\/p>\n<p><b>Chi-Square Tests<\/b>:This test is used to determine whether there is significant difference in between the expected frequencies and the observed frequencies in one or more categories.<\/p>\n<div style=\"text-align: center;\"><span style=\"color: #990000;\"><span style=\"font-size: large;\"><b>Categories of Non-Parametric Tests<\/b><\/span><\/span><\/div>\n<p>Non-Parametric tests could be categorized into three different categories as shown below:<\/p>\n<ul>\n<li><span style=\"color: #990000;\"><i>Goodness of Fit Tests<\/i>:<\/span> In this categories, the distribution of the variable being analyzed is the same as hypothetical<\/li>\n<li><span style=\"color: #990000;\"><i>Tests for Independence<\/i>:<\/span> Here, the claim is that the rows and columns of variables being tested are independent.<\/li>\n<li><span style=\"color: #990000;\"><i>Tests for Homogeneity<\/i><\/span>: In tests for homogeneity, the variables being analyzed are distributed equally<\/li>\n<\/ul>\n<p>Table 1.0 summarized the three categories of non-parametric tests<\/p>\n<div style=\"clear: both; text-align: center;\"><a style=\"margin-left: 1em; margin-right: 1em;\" href=\"https:\/\/1.bp.blogspot.com\/-L_TK8gI59xo\/WqHQMnbJEFI\/AAAAAAAABKc\/IyiGM5HJvpUALj5mkCOJAcAhCSkP9YIEACLcBGAs\/s1600\/Non-Parametric%2BTests.jpg\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/1.bp.blogspot.com\/-L_TK8gI59xo\/WqHQMnbJEFI\/AAAAAAAABKc\/IyiGM5HJvpUALj5mkCOJAcAhCSkP9YIEACLcBGAs\/s640\/Non-Parametric%2BTests.jpg\" width=\"640\" height=\"363\" border=\"0\" data-original-height=\"565\" data-original-width=\"991\" \/><\/a><\/div>\n<div style=\"text-align: center;\">Table 1.0: Summary of Non-Parametric Tests<\/div>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Non-parametric tests which are also called distribution-free tests are applied when the distribution of the population is not known. In other words, non-parametric tests makes &hellip; <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0},"categories":[223],"tags":[],"_links":{"self":[{"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/posts\/147"}],"collection":[{"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/comments?post=147"}],"version-history":[{"count":2,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/posts\/147\/revisions"}],"predecessor-version":[{"id":913,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/posts\/147\/revisions\/913"}],"wp:attachment":[{"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/media?parent=147"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/categories?post=147"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/tags?post=147"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}