{"id":154018,"date":"2022-03-25T23:04:07","date_gmt":"2022-03-25T17:34:07","guid":{"rendered":"https:\/\/infinitylearn.com\/surge\/non-parametric-test-formula-and-types\/"},"modified":"2023-01-02T14:59:56","modified_gmt":"2023-01-02T09:29:56","slug":"non-parametric-test-formula-and-types","status":"publish","type":"post","link":"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/","title":{"rendered":"Non Parametric Test \u2013 Formula and Types"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_37 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" style=\"display: none;\"><label for=\"item\" aria-label=\"Table of Content\"><span style=\"display: flex;align-items: center;width: 35px;height: 30px;justify-content: center;\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/label><input type=\"checkbox\" id=\"item\"><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' style='display:block'><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/#What_is_a_Non_Parametric_Test\" title=\"What is a Non Parametric Test?\">What is a Non Parametric Test?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/#Parametric_Test_and_Nonparametric_Test\" title=\"Parametric Test and Nonparametric Test\">Parametric Test and Nonparametric Test<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/#Non_Parametric_Test_Formula\" title=\"Non Parametric Test Formula\">Non Parametric Test Formula<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/#Types_of_Non_Parametric_Test\" title=\"Types of Non Parametric Test\">Types of Non Parametric Test<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/#Non_Parametric_Test_Advantages_and_Disadvantages\" title=\"Non Parametric Test Advantages and Disadvantages\">Non Parametric Test Advantages and Disadvantages<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/#The_Disadvantages_of_Non_Parametric_Test_are_as_follows\" title=\"The Disadvantages of Non Parametric Test are as follows:\">The Disadvantages of Non Parametric Test are as follows:<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/#Hypothesis_Significance\" title=\"Hypothesis Significance\">Hypothesis Significance<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/#Hypothesis_Testing\" title=\"Hypothesis Testing\">Hypothesis Testing<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/#Table_of_Contents\" title=\"Table of Contents\">Table of Contents<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/#Parametric_Tests\" title=\"Parametric Tests\">Parametric Tests<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/#Non-Parametric_tests_in_Statistics\" title=\"Non-Parametric tests in Statistics\">Non-Parametric tests in Statistics<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/#Applications_of_Non-Parametric_Test\" title=\"Applications of Non-Parametric Test\">Applications of Non-Parametric Test<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"What_is_a_Non_Parametric_Test\"><\/span>What is a Non Parametric Test?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>A nonparametric test is a statistical test that does not rely on the assumption of a normal distribution. This type of test is used when the data does not meet the requirements of a parametric test. Nonparametric tests are usually less powerful than parametric tests, but they are also less sensitive to violations of the normality assumption.<\/p>\n<p><img loading=\"lazy\" class=\"aligncenter wp-image-154017 size-medium\" src=\"https:\/\/infinitylearn.com\/surge\/wp-content\/uploads\/2022\/03\/non-parametric-test-formula-and-types-300x212.jpg\" alt=\"Non Parametric Test \" width=\"300\" height=\"212\" srcset=\"https:\/\/infinitylearn.com\/surge\/wp-content\/uploads\/2022\/03\/non-parametric-test-formula-and-types-300x212.jpg?v=1648229642 300w, https:\/\/infinitylearn.com\/surge\/wp-content\/uploads\/2022\/03\/non-parametric-test-formula-and-types.jpg?v=1648229642 606w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Parametric_Test_and_Nonparametric_Test\"><\/span>Parametric Test and Nonparametric Test<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Parametric testing is a type of statistical hypothesis testing in which the test statistic is assumed to be drawn from a certain family of distributions. Nonparametric testing is a type of statistical hypothesis testing in which the test statistic is not assumed to be drawn from any particular family of distributions.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Non_Parametric_Test_Formula\"><\/span>Non Parametric Test Formula<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>A nonparametric test is a statistical test that does not require the assumption of a normal distribution. Nonparametric tests are typically used when the data are not normally distributed or when the sample size is small.<\/p>\n<p>There are many different types of nonparametric tests, but the most common is the Wilcoxon rank-sum test. The Wilcoxon rank-sum test is used to compare two groups of data. The test determines whether the two groups are statistically different from each other.<\/p>\n<p>The Wilcoxon rank-sum test is a two-tailed test, which means that it can detect differences in either direction. The test is also non-directional, which means that it is not specific about the direction of the difference.<\/p>\n<p>The Wilcoxon rank-sum test is a hypothesis test. The test compares the two groups of data and determines whether the difference between the groups is statistically significant. To perform the Wilcoxon rank-sum test, you first need to calculate the rank of each data point in each group. The ranks are then summed for each group. The group with the higher sum is considered to have the larger sample size.<\/p>\n<p>The Wilcoxon rank-sum test statistic is then calculated. The statistic is a measure of the difference between the two groups. The statistic is compared to a chi-squared distribution to determine whether the difference is statistically significant.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Types_of_Non_Parametric_Test\"><\/span>Types of Non Parametric Test<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>There are five types of non parametric tests:<\/p>\n<p>1. Chi-square test<br \/>\n2. Mann-Whitney U test<br \/>\n3. Kruskal-Wallis H test<br \/>\n4. Wilcoxon signed-rank test<br \/>\n5. Friedman test<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Non_Parametric_Test_Advantages_and_Disadvantages\"><\/span>Non Parametric Test Advantages and Disadvantages<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Non parametric tests are advantageous because they are less likely to be influenced by the distribution of the data. They are also easier to use than parametric tests.<\/p>\n<p>Non parametric tests are disadvantageous because they are less powerful than parametric tests.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_Disadvantages_of_Non_Parametric_Test_are_as_follows\"><\/span>The Disadvantages of Non Parametric Test are as follows:<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>1. Non parametric tests are less powerful than parametric tests.<\/p>\n<p>2. Non parametric tests are not as widely accepted as parametric tests.<\/p>\n<p>3. Non parametric tests are less versatile than parametric tests.<\/p>\n<p>4. Non parametric tests are more difficult to use than parametric tests.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Hypothesis_Significance\"><\/span>Hypothesis Significance<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The null hypothesis is that there is no significant difference between the two treatments.<\/p>\n<p>The significance of the difference between the two treatments is 0.023.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Hypothesis_Testing\"><\/span>Hypothesis Testing<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Null Hypothesis: The average height of all males is the same.<\/p>\n<p>Alternative Hypothesis: The average height of all males is not the same.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Table_of_Contents\"><\/span>Table of Contents<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>1. Introduction<br \/>\n2. Theoretical Framework<br \/>\n2.1. Game Theory<br \/>\n2.2. Nash Equilibrium<br \/>\n3. Empirical Analysis<br \/>\n3.1. Data and Methodology<br \/>\n3.2. Results<br \/>\n4. Conclusion<\/p>\n<p>1. Introduction<\/p>\n<p>The purpose of this paper is to empirically investigate the impact of trade liberalization on regional trade blocs. In particular, the paper seeks to answer the following question: do trade blocs become more or less active following a trade liberalization event?<\/p>\n<p>To answer this question, the paper employs a game theoretic approach, specifically the Nash equilibrium. The Nash equilibrium is a concept from game theory that describes a situation in which each player in a game has chosen a best strategy given the strategies of the other players. The Nash equilibrium is important in the context of trade blocs because it allows us to understand how blocs will behave in the presence of liberalization.<\/p>\n<p>The paper finds that trade blocs become more active following a trade liberalization event. This finding is significant because it suggests that trade blocs are an important tool for countries looking to increase trade.<\/p>\n<p>2. Theoretical Framework<\/p>\n<p>In order to understand the impact of trade liberalization on trade blocs, it is necessary to first understand the theoretical framework underlying trade blocs. This section will discuss two key concepts from game theory that are relevant to this topic: the<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Parametric_Tests\"><\/span>Parametric Tests<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The chi-squared statistic is used in a number of different parametric tests.<\/p>\n<p>The chi-squared statistic can be used to test the null hypothesis that two or more independent samples are drawn from the same population.<\/p>\n<p>The chi-squared statistic can be used to test the null hypothesis that a population is binomial.<\/p>\n<p>The chi-squared statistic can be used to test the null hypothesis that a population is Poisson.<\/p>\n<p>The chi-squared statistic can be used to test the null hypothesis that a population is normal.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Non-Parametric_tests_in_Statistics\"><\/span>Non-Parametric tests in Statistics<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Non-parametric tests are tests that don&#8217;t rely on any assumptions about the population distribution. This makes them less sensitive to departures from the norm, and they can be used even when the population is not normal.<\/p>\n<p>There are a number of different non-parametric tests, but the most common are the chi-square test, the Mann-Whitney U test, and the Kruskal-Wallis H test.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Applications_of_Non-Parametric_Test\"><\/span>Applications of Non-Parametric Test<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>1. To compare the means of two groups<\/p>\n<p>2. To compare the proportions of two groups<\/p>\n<p>3. To compare the median of two groups<\/p>\n<p>4. To compare the variability of two groups<\/p>\n","protected":false},"excerpt":{"rendered":"<p>What is a Non Parametric Test? A nonparametric test is a statistical test that does not rely on the assumption [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_yoast_wpseo_focuskw":"Non Parametric Test \u2013 Formula and Types","_yoast_wpseo_title":"","_yoast_wpseo_metadesc":"Learn about Non Parametric Test topic of Maths in details explained by subject experts on infinitylearn.com.","custom_permalink":"maths\/non-parametric-test\/"},"categories":[13],"tags":[],"table_tags":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v17.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Non Parametric Test \u2013 Formula and Types - Infinity Learn by Sri Chaitanya<\/title>\n<meta name=\"description\" content=\"Learn about Non Parametric Test topic of Maths in details explained by subject experts on infinitylearn.com.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/infinitylearn.com\/surge\/maths\/non-parametric-test\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Non Parametric Test \u2013 Formula and Types - 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