{"id":179523,"date":"2024-02-28T16:09:14","date_gmt":"2024-02-28T15:09:14","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=179523"},"modified":"2024-02-22T19:07:27","modified_gmt":"2024-02-22T18:07:27","slug":"understanding-kurtosis-calculating-outlier-frequency-in-statistical-distributions","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/understanding-kurtosis-calculating-outlier-frequency-in-statistical-distributions","title":{"rendered":"Understanding Kurtosis: Calculating Outlier Frequency in Statistical Distributions"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"179523\" class=\"elementor elementor-179523\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-89a94d5 e-flex e-con-boxed e-con\" data-id=\"89a94d5\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-23ca5d1 elementor-widget elementor-widget-heading\" data-id=\"23ca5d1\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h2 class=\"elementor-heading-title elementor-size-default\">The quality of machine learning performance depends largely on the information available. That's why Data Scientists need to carefully study the datasets they use. To do this, they have a wide range of statistical tools at their disposal. One of these is kurtosis. So what is kurtosis? What's it used for? Find out the answers.<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-bf838d9 e-flex e-con-boxed e-con\" data-id=\"bf838d9\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f493216 elementor-widget elementor-widget-heading\" data-id=\"f493216\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What is Kurtosis?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-89bc0b7 elementor-widget elementor-widget-text-editor\" data-id=\"89bc0b7\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p>Coming from the<strong> ancient Greek name \u03ba\u03cd\u03c1\u03c4\u03c9\u03c3\u03b9\u03c2 (meaning curvature), Kurtosis<\/strong> is a<a href=\"https:\/\/datascientest.com\/en\/altair-everything-you-need-to-know-about-this-statistical-visualization-library\"> statistical tool<\/a> for measuring the sharpness and kurtosis of the distribution of a real random value.<\/p><p><strong>Kurtosis<\/strong> corresponds to the probability and\/or frequency of occurrence of outliers (i.e. values that are extremely high or extremely low in relation to the mean). On a curve, this represents the extremities on either side of a distribution.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-75a1c41 elementor-widget elementor-widget-text-editor\" data-id=\"75a1c41\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Good to know:<\/strong> we also speak of acuity coefficient, flattening coefficient and degree of curvature.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-041afff elementor-widget elementor-widget-image\" data-id=\"041afff\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/07\/kurtosis.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-d91d646 e-flex e-con-boxed e-con\" data-id=\"d91d646\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5b028f6 elementor-widget elementor-widget-heading\" data-id=\"5b028f6\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What are the different types of Kurtosis?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-673fa88 elementor-widget elementor-widget-text-editor\" data-id=\"673fa88\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Depending on their degree of flattening, distributions can be classified into 3 categories.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-62608cb elementor-widget elementor-widget-heading\" data-id=\"62608cb\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Mesokurtic distributions<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-61d14ec elementor-widget elementor-widget-text-editor\" data-id=\"61d14ec\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>These are <strong>distributions<\/strong> with average kurtosis. In other words, outliers are neither very frequent nor very rare.<\/p><p><strong>Kurtosis<\/strong> is always measured in relation to normal <strong>Kurtosis<\/strong>. In principle, the normal distribution has a Kurtosis of 3. If this is the case, all distributions with a similar Kurtosis will be considered mesokurtic.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1a241a3 elementor-widget elementor-widget-text-editor\" data-id=\"1a241a3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Good to know:<\/strong> Kurtosis is often described by an excess of Kurtosis, i.e. -3. This excess flattening makes it easier to compare distributions with the norm. But here, the excess of normal Kurtosis has a value equal to 0. And here again, all distributions with a Kurtosis close to 0 will be considered mesokurtic.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7c459a0 elementor-widget elementor-widget-text-editor\" data-id=\"7c459a0\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>This type of distribution applies, for example, to the birth weight of babies. Even if there are outliers (5 or 2 kilograms at birth), they are neither very frequent nor very infrequent.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-78b8ee3 elementor-widget elementor-widget-image\" data-id=\"78b8ee3\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/07\/mesocurtique.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9561112 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"9561112\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/en\/data-courses\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Training in Data Science<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-46dd395 e-flex e-con-boxed e-con\" data-id=\"46dd395\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-829ebdf elementor-widget elementor-widget-heading\" data-id=\"829ebdf\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Platykurtic distributions<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d3be6b5 elementor-widget elementor-widget-text-editor\" data-id=\"d3be6b5\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>These are distributions with low <strong>kurtosis (fine tails).<\/strong> This means that outliers are very infrequent.<\/p><p>In this case, Kurtosis is lower than in a normal distribution. It is less than 3, and the<strong> excess Kurtosis<\/strong> less than 0. This is why we also speak of negative kurtosis, since the excess kurtosis is negative.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f5ad214 elementor-widget elementor-widget-text-editor\" data-id=\"f5ad214\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Good to know:<\/strong> the name PlatyKurtosis (and more precisely the term platy) comes from the Greek plat\u00fas, meaning flat. This is because many platykurtic distributions have a flattened peak, although some may be pointed. But <strong>Kurtosis<\/strong> measures the length of the flattening (the two ends of the distribution), not the &#8220;peak&#8221;. PlatyKurtosis therefore comes from a confusion on the part of the statisticians of the time, but the term has stuck.<\/p><p>\u00a0<\/p><p>\ud83d\udca1Related articles:<\/p><table dir=\"ltr\" border=\"1\" cellspacing=\"0\" cellpadding=\"0\" data-sheets-root=\"1\"><colgroup><col width=\"656\" \/><\/colgroup><tbody><tr><td data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;Alta\u00efr: everything you need to know about this statistical visualization library&quot;}\" data-sheets-hyperlink=\"https:\/\/datascientest.com\/en\/altair-everything-you-need-to-know-about-this-statistical-visualization-library\"><a class=\"in-cell-link\" href=\"https:\/\/datascientest.com\/en\/altair-everything-you-need-to-know-about-this-statistical-visualization-library\" target=\"_blank\" rel=\"noopener\">Alta\u00efr: everything you need to know about this statistical visualization library<\/a><\/td><\/tr><tr><td data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;Chi squared test: Find out more about this essential statistical test&quot;}\" data-sheets-hyperlink=\"https:\/\/datascientest.com\/en\/chi-squared-test-find-out-more-about-this-essential-statistical-test\"><a class=\"in-cell-link\" href=\"https:\/\/datascientest.com\/en\/chi-squared-test-find-out-more-about-this-essential-statistical-test\" target=\"_blank\" rel=\"noopener\">Chi squared test: Find out more about this essential statistical test<\/a><\/td><\/tr><tr><td data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;4 types of statistical bias to avoid in your analyses&quot;}\" data-sheets-hyperlink=\"https:\/\/datascientest.com\/en\/4-types-of-statistical-bias-to-avoid-in-your-analyses\"><a class=\"in-cell-link\" href=\"https:\/\/datascientest.com\/en\/4-types-of-statistical-bias-to-avoid-in-your-analyses\" target=\"_blank\" rel=\"noopener\">4 types of statistical bias to avoid in your analyses<\/a><\/td><\/tr><tr><td data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;3 Examples for understanding non-parametric statistical tests&quot;}\" data-sheets-hyperlink=\"https:\/\/datascientest.com\/en\/3-examples-for-understanding-non-parametric-statistical-tests\"><a class=\"in-cell-link\" href=\"https:\/\/datascientest.com\/en\/3-examples-for-understanding-non-parametric-statistical-tests\" target=\"_blank\" rel=\"noopener\">3 Examples for understanding non-parametric statistical tests<\/a><\/td><\/tr><\/tbody><\/table>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d15b21e elementor-widget elementor-widget-text-editor\" data-id=\"d15b21e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>On a curve, a<strong> platykurtic distribution<\/strong> generally means a uniform distribution. There is almost no variation between the different variables.<\/p><p>This would be the case, for example, in a study of high school students&#8217; use of social networks. Here, they are almost all the same age, and use almost all social media equally, whatever their age. There are few or no outliers (in a high school, few students would be over 18 or under 14).<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-971e2b6 elementor-widget elementor-widget-image\" data-id=\"971e2b6\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/07\/platycurtique.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-51bc8e2 elementor-widget elementor-widget-heading\" data-id=\"51bc8e2\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Leptokurtic distributions<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-905b4aa elementor-widget elementor-widget-text-editor\" data-id=\"905b4aa\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>These are distributions with a high degree of <strong>kurtosis<\/strong> (also known as wide-tail distributions). In other words, there are many outliers. They are therefore higher than a normal distribution. This translates into a Kurtosis greater than 3 and an excess Kurtosis greater than 0. Here, we speak of positive Kurtosis.<\/p><p>A<strong> leptokurtic distribution<\/strong> could, for example, concern the Earth&#8217;s distance from other stars in the universe. Some are relatively close (or at least accessible), while others are hundreds of light-years away.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-79d1737 elementor-widget elementor-widget-image\" data-id=\"79d1737\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/07\/leptocurtique.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6a9b23d e-flex e-con-boxed e-con\" data-id=\"6a9b23d\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6bb1025 elementor-widget elementor-widget-heading\" data-id=\"6bb1025\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What is Kurtosis used for?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e8b8ad9 elementor-widget elementor-widget-text-editor\" data-id=\"e8b8ad9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>By determining the disparity of values within a distribution, <strong>Kurtosis<\/strong> is one of the essential statistical tools. It can be applied to a wide variety of business sectors.<\/p><p>Here are the most common:<\/p><ul><li><a href=\"https:\/\/datascientest.com\/en\/synergies-unveiled-the-dynamic-intersection-of-data-science-and-finance\"><strong>Financial analysis:<\/strong> <\/a>Kurtosis is used to measure the risk of price volatility of an investment. If Kurtosis is high (in the case of a leptokurtic distribution), this means that the chosen investment will occasionally produce extreme returns. This can lead to exponential gains, but also to significant losses. Conversely, an equity portfolio with a low Kurtosis value indicates a more stable and predictable return. This means less risk, but also less profit.<\/li><li><a href=\"https:\/\/datascientest.com\/en\/machine-learning-engineer-bootcamp-why-is-it-interesting\"><strong>Machine learning:<\/strong><\/a> the aim here is to measure the disparity of a data set. This does not mean, however, that the available data is bad. The idea is above all to enable data scientists to better understand the dataset in order to improve the performance of machine learning.<\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-4eb281e e-flex e-con-boxed e-con\" data-id=\"4eb281e\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6433b8c elementor-widget elementor-widget-heading\" data-id=\"6433b8c\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What are the differences between Skewness and Kurtosis?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d952250 elementor-widget elementor-widget-text-editor\" data-id=\"d952250\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>To measure the disparity of a <a href=\"https:\/\/datascientest.com\/en\/datasets-top-5-places-to-find-quality-datasets\">dataset<\/a>, Data Scientists can use Kurtosis or Skewness. In the latter case, the focus is on measuring the spread of the distribution around the central value. Conversely, Kurtosis measures the frequency of outliers.<\/p><p>But in both cases, they are essential measurement tools for machine learning.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-ebe210f e-flex e-con-boxed e-con\" data-id=\"ebe210f\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-0ca2e7d elementor-widget elementor-widget-heading\" data-id=\"0ca2e7d\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Want to find out more about Machine Learning?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1a7d19f elementor-widget elementor-widget-text-editor\" data-id=\"1a7d19f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Beyond statistical tools, Machine Learning requires a wide range of skills in predictive analysis, computer language, <a href=\"https:\/\/datascientest.com\/en\/refactoring-databases-and-code-comprehensive-guide-to-the-essentials\">databases<\/a>, etc. As such, training in data science is more than necessary. That&#8217;s why we created the <strong>Data Scientist training course.<\/strong> Find out more!<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-49c7b4b elementor-widget__width-initial elementor-widget elementor-widget-video\" data-id=\"49c7b4b\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/datascientest.com\\\/en\\\/data-scientist-course&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-video .elementor-widget-container{overflow:hidden;transform:translateZ(0)}.elementor-widget-video .elementor-wrapper{aspect-ratio:var(--video-aspect-ratio)}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{height:100%;width:100%;display:flex;border:none;background-color:#000}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-wrapper{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .elementor-open-inline .elementor-custom-embed-image-overlay{position:absolute;top:0;right:0;bottom:0;left:0;background-size:cover;background-position:50%}.elementor-widget-video .elementor-custom-embed-image-overlay{cursor:pointer;text-align:center}.elementor-widget-video .elementor-custom-embed-image-overlay:hover .elementor-custom-embed-play i{opacity:1}.elementor-widget-video .elementor-custom-embed-image-overlay img{display:block;width:100%;aspect-ratio:var(--video-aspect-ratio);-o-object-fit:cover;object-fit:cover;-o-object-position:center center;object-position:center center}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-custom-embed-image-overlay{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-custom-embed-image-overlay img{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .e-hosted-video .elementor-video{-o-object-fit:cover;object-fit:cover}.e-con-inner>.elementor-widget-video,.e-con>.elementor-widget-video{width:var(--container-widget-width);--flex-grow:var(--container-widget-flex-grow)}<\/style>\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dcf3471 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"dcf3471\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/en\/data-scientist-course\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Find out more about our Data Scientist training<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-d1adf8e e-flex e-con-boxed e-con\" data-id=\"d1adf8e\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-12d2f2a elementor-widget elementor-widget-html\" data-id=\"12d2f2a\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [{\n    \"@type\": \"Question\",\n    \"name\": \"What is Kurtosis?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"Coming from the ancient Greek name \u03ba\u03cd\u03c1\u03c4\u03c9\u03c3\u03b9\u03c2 (meaning curvature), Kurtosis is a statistical tool for measuring the sharpness and kurtosis of the distribution of a true random value.\"\n    }\n  },{\n    \"@type\": \"Question\",\n    \"name\": \"What are the different types of Kurtosis?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"These are the distributions with average kurtosis. In other words, outliers are neither very frequent nor very rare. Kurtosis is always measured in relation to normal Kurtosis. In principle, the normal distribution has a Kurtosis of 3. If this is the case, all distributions with a similar Kurtosis will be considered mesokurtic.\"\n    }\n  },{\n    \"@type\": \"Question\",\n    \"name\": \"What is the purpose of Kurtosis?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"Financial analysis: Kurtosis measures the risk of price volatility of an investment. If Kurtosis is high (in the case of a leptokurtic distribution), this means that the chosen investment will occasionally produce extreme returns. This can lead to exponential gains, but also to significant losses. Conversely, an equity portfolio with a low Kurtosis value indicates a more stable and predictable return. 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[&hellip;]<\/p>\n","protected":false},"author":67,"featured_media":179525,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2425],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Understanding Kurtosis: Calculating Outlier Frequency in Statistical Distributions<\/title>\n<meta name=\"description\" content=\"Learn how to calculate the frequency of outliers using kurtosis, a statistical measure that quantifies the shape of a distribution, and explore its implications for data analysis and outlier detection.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datascientest.com\/en\/understanding-kurtosis-calculating-outlier-frequency-in-statistical-distributions\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Understanding Kurtosis: Calculating Outlier Frequency in Statistical Distributions\" \/>\n<meta property=\"og:description\" content=\"The quality of machine learning performance depends largely on the information available. 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