{"id":20401,"date":"2025-03-17T06:32:52","date_gmt":"2025-03-17T06:32:52","guid":{"rendered":"https:\/\/www.pickl.ai\/blog\/?p=20401"},"modified":"2025-03-17T06:32:53","modified_gmt":"2025-03-17T06:32:53","slug":"quartile-deviation","status":"publish","type":"post","link":"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/","title":{"rendered":"The Power of Quartile Deviation: Unlocking Data Dispersion Secrets"},"content":{"rendered":"\n<p><strong>Summary:<\/strong> Quartile deviation is a statistical measure that quantifies data spread by focusing on the middle 50% of the data, offering robustness to outliers and skewed distributions. It is calculated as half the difference between the third and first quartiles, providing a reliable measure of central data dispersion.<\/p>\n\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 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\" style=\"cursor:inherit\">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\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><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><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Introduction\" >Introduction<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Introduction_to_Quartile_Deviation\" >Introduction to Quartile Deviation<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Understanding_Quartiles\" >Understanding Quartiles<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Calculating_Quartile_Deviation\" >Calculating Quartile Deviation<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Example_1_Ungrouped_Data\" >Example 1: Ungrouped Data<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Example_2_Grouped_Data\" >Example 2: Grouped Data<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Robustness_to_Outliers_The_Power_of_Quartile_Deviation\" >Robustness to Outliers: The Power of Quartile Deviation<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Understanding_Quartile_Deviation\" >Understanding Quartile Deviation<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Robustness_to_Outliers\" >Robustness to Outliers<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Advantages_of_Quartile_Deviation\" >Advantages of Quartile Deviation<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Easy_Calculation_and_Interpretation\" >Easy Calculation and Interpretation<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Robustness_to_Outliers-2\" >Robustness to Outliers<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Superior_to_Range\" >Superior to Range<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Applicability_in_Open-End_Distributions\" >Applicability in Open-End Distributions<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Utility_in_Skewed_Distributions\" >Utility in Skewed Distributions<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Shortcut_for_Standard_Deviation\" >Shortcut for Standard Deviation<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Conclusion\" >Conclusion<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#Frequently_Asked_Questions\" >Frequently Asked Questions<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#What_Is_Quartile_Deviation_Used_For\" >What Is Quartile Deviation Used For?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-20\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#How_Does_Quartile_Deviation_Differ_from_Standard_Deviation\" >How Does Quartile Deviation Differ from Standard Deviation?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-21\" href=\"https:\/\/www.pickl.ai\/blog\/quartile-deviation\/#What_are_the_Advantages_of_Using_Quartile_Deviation\" >What are the Advantages of Using Quartile Deviation?<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2 id=\"introduction\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Introduction\"><\/span><strong>Introduction<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>In the vast and intricate world of <a href=\"https:\/\/pickl.ai\/blog\/empirical-formula-statistics\/\">statistics<\/a>, understanding how data spreads out or disperses is crucial for making informed decisions. Among the various measures of dispersion, <strong>quartile deviation<\/strong> stands out as a powerful tool for analysing data distribution.<\/p>\n\n\n\n<p>It is particularly useful when dealing with datasets that contain outliers, as it focuses on the middle 50% of the data, providing a clearer picture of the data&#8217;s central tendency.&nbsp;<\/p>\n\n\n\n<p>In this blog, we will delve into the concept of quartile deviation, explore its formula, and examine practical examples to illustrate its application.<\/p>\n\n\n\n<h2 id=\"introduction-to-quartile-deviation\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Introduction_to_Quartile_Deviation\"><\/span><strong>Introduction to Quartile Deviation<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Quartile <a href=\"https:\/\/pickl.ai\/blog\/standard-deviation-how-to-calculate\/\">deviation<\/a>, also known as the semi-interquartile range, is a statistical measure that quantifies the dispersion of data by focusing on the difference between the third quartile (Q3) and the first quartile (Q1). This difference is then halved to obtain the quartile deviation. The formula for quartile deviation is straightforward:<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/lh7-rt.googleusercontent.com\/docsz\/AD_4nXdEKrL8Pk_jmhykWjdAGS4sYaL6KQMMesnh2Pln5cilQlbWxQX05H0x3HtsmUj4sfPqlTIhvy1DPX4kwoUy05wIWZZ2i6buWfSOL0qkzjIE_aORkDGBffRZrgxAfw-1LO2QqqoUfA?key=7Xx9bKBODIL2u2puCk-3pZas\" alt=\"formula of Quartile Deviation\"\/><\/figure>\n\n\n\n<p>This measure is particularly useful for understanding the spread of data in the middle range, excluding the extreme values that might skew other measures like the standard deviation.<\/p>\n\n\n\n<h2 id=\"understanding-quartiles\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Understanding_Quartiles\"><\/span><strong>Understanding Quartiles<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Before diving deeper into quartile deviation, it&#8217;s essential to grasp what quartiles are. Quartiles divide a dataset into four equal parts:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>First Quartile (Q1):<\/strong> The median of the lower half of the data, representing the 25th percentile.<\/li>\n\n\n\n<li><strong>Second Quartile (Q2):<\/strong> The median of the entire dataset.<\/li>\n\n\n\n<li><strong>Third Quartile (Q3):<\/strong> The median of the upper half of the data, representing the 75th percentile.<\/li>\n<\/ul>\n\n\n\n<h2 id=\"calculating-quartile-deviation\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Calculating_Quartile_Deviation\"><\/span><strong>Calculating Quartile Deviation<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>To calculate quartile deviation, follow these steps:<\/p>\n\n\n\n<p><strong>Step 1: Arrange Data in Ascending Order:<\/strong> Ensure your dataset is sorted from smallest to largest.<\/p>\n\n\n\n<p><strong>Step 2: Identify Q1 and Q3:<\/strong> Calculate the first and third quartiles based on the dataset&#8217;s size.<\/p>\n\n\n\n<p><strong>Step 3: Apply the Formula:<\/strong> Use the formula Q.D.=Q3\u2212Q12Q.D.=2<em>Q<\/em>3\u2212<em>Q<\/em>1 to find the quartile deviation.<\/p>\n\n\n\n<h3 id=\"example-1-ungrouped-data\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Example_1_Ungrouped_Data\"><\/span><strong>Example 1: Ungrouped Data<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Consider a dataset of exam scores: 70, 85, 90, 78, 92, 88, 76, 95, 89.<\/p>\n\n\n\n<p><strong>Step 1: Arrange Data:<\/strong> 70, 76, 78, 85, 88, 89, 90, 92, 95.<\/p>\n\n\n\n<p><strong>Step 2: Find Q1 and Q3:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Q1 is the median of the lower half: 76, 78, 85. Thus, Q1 = 78.<\/li>\n\n\n\n<li>Q3 is the median of the upper half: 88, 89, 90, 92, 95. Thus, Q3 = 90.\u00a0<\/li>\n<\/ul>\n\n\n\n<p><strong>Step 3: Calculate <\/strong>QD: Q.D= 90-78\/2=6<\/p>\n\n\n\n<h3 id=\"example-2-grouped-data\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Example_2_Grouped_Data\"><\/span><strong>Example 2: Grouped Data<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>For grouped data, the process involves calculating cumulative frequencies and using them to estimate Q1 and Q3.<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/lh7-rt.googleusercontent.com\/docsz\/AD_4nXfh4dMSO8WTKyYFXgOTcU5OhbUoeC-_l36AGBykLLP28kN-PSuwBJuEo5uFdARc_qxPs1RLNa1vIHxVu9rg70DqsX36eXSkHQEGqrMGrgVNTMkiZsO8WO4uAOCJrnOOeqAuJc5bUA?key=7Xx9bKBODIL2u2puCk-3pZas\" alt=\"table of Grouped Data\"\/><\/figure>\n\n\n\n<p><strong>Step 1: Calculate Cumulative Frequencies:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>0-10: 5<\/li>\n\n\n\n<li>10-20: 8<\/li>\n\n\n\n<li>20-30: 12<\/li>\n\n\n\n<li>30-40: 15<\/li>\n\n\n\n<li>40-50: 18<\/li>\n<\/ul>\n\n\n\n<p><strong>Step 2: Find Q1 and Q3:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Q1 lies in the class 10-20, as the cumulative frequency exceeds N\/4 here.<\/li>\n\n\n\n<li>Q3 lies in the class 30-40, as it exceeds 3N\/4.<\/li>\n<\/ul>\n\n\n\n<p><strong>Step 3: Estimate Q1 and Q3:<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/lh7-rt.googleusercontent.com\/docsz\/AD_4nXemsiPjCBiO50gi2C8NK96KmjtXMfQ2aHWPcFpKfpLglJUWUGs_cgDXMlw-AroZxCcbcj6_3cjkLD7Gwl4BP5nnBmIt3kt3ceIjh7njh0F9ckkOHRHGtoWPYHjsYBmNagYIi715?key=7Xx9bKBODIL2u2puCk-3pZas\" alt=\"\"\/><\/figure>\n\n\n\n<p><strong>Step 4: Calculate: <\/strong>QD: Q.D= 35-10\/2= 12.5<\/p>\n\n\n\n<h2 id=\"robustness-to-outliers-the-power-of-quartile-deviation\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Robustness_to_Outliers_The_Power_of_Quartile_Deviation\"><\/span><strong>Robustness to Outliers: The Power of Quartile Deviation<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>In <a href=\"https:\/\/pickl.ai\/blog\/parameters-in-statistical-analysis\/\">statistical analysis<\/a>, dealing with outliers is a common challenge. Outliers are data points that significantly deviate from the rest of the data, potentially skewing statistical measures like the mean and standard deviation. One robust measure that effectively handles outliers is quartile deviation.&nbsp;<\/p>\n\n\n\n<h3 id=\"understanding-quartile-deviation\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Understanding_Quartile_Deviation\"><\/span><strong>Understanding Quartile Deviation<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>It also known as the semi-interquartile range, is calculated as half the difference between the third quartile (Q3) and the first quartile (Q1) of a dataset.\u00a0<\/p>\n\n\n\n<p>This measure focuses on the middle 50% of the data, making it less sensitive to extreme values or outliers compared to other dispersion measures like the range or standard deviation.<\/p>\n\n\n\n<h3 id=\"robustness-to-outliers\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Robustness_to_Outliers\"><\/span><strong>Robustness to Outliers<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>The robustness of quartile deviation to outliers stems from its focus on the interquartile range (IQR), which encompasses the central portion of the data.&nbsp;<\/p>\n\n\n\n<p>Unlike the standard deviation, which can be heavily influenced by a single outlier, It remains stable even when outliers are present. This makes it particularly useful for analysing datasets with skewed distributions or outliers.<\/p>\n\n\n\n<h2 id=\"advantages-of-quartile-deviation\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Advantages_of_Quartile_Deviation\"><\/span><strong>Advantages of Quartile Deviation<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>It also known as the semi-interquartile range, offers several advantages in statistical analysis, particularly when dealing with datasets that contain outliers or have skewed distributions. Here are some of the key benefits:<\/p>\n\n\n\n<h3 id=\"easy-calculation-and-interpretation\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Easy_Calculation_and_Interpretation\"><\/span><strong>Easy Calculation and Interpretation<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>It is straightforward to calculate and understand. The formula, Q.D.=Q3\u2212Q12Q.D.=2<em>Q<\/em>3\u2212<em>Q<\/em>1, is simple and intuitive, making it accessible to those without extensive statistical knowledge.<\/p>\n\n\n\n<h3 id=\"robustness-to-outliers-2\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Robustness_to_Outliers-2\"><\/span><strong>Robustness to Outliers<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>One of the most significant advantages is robustness to outliers. Since it focuses on the middle 50% of the data, extreme values do not significantly impact its calculation, providing a more reliable measure of dispersion in skewed distributions.<\/p>\n\n\n\n<h3 id=\"superior-to-range\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Superior_to_Range\"><\/span><strong>Superior to Range<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>It is consider superior to the range because it is based on the middle 50% of the data, rather than just the minimum and maximum values. This makes it less sensitive to outliers and provides a more accurate representation of data spread.<\/p>\n\n\n\n<h3 id=\"applicability-in-open-end-distributions\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Applicability_in_Open-End_Distributions\"><\/span><strong>Applicability in Open-End Distributions<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>It determined even in open-end distributions or when data ranked but not quantitatively measured. This flexibility is particularly useful in scenarios where other measures of dispersion might not be applicable.<\/p>\n\n\n\n<h3 id=\"utility-in-skewed-distributions\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Utility_in_Skewed_Distributions\"><\/span><strong>Utility in Skewed Distributions<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>In datasets with skewed distributions, It is especially useful. It helps in understanding the spread of the central portion of the data without influenced by extreme values, making it a valuable tool for analysing such datasets.<\/p>\n\n\n\n<h3 id=\"shortcut-for-standard-deviation\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Shortcut_for_Standard_Deviation\"><\/span><strong>Shortcut for Standard Deviation<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Quartile deviation can also used as a shortcut to estimate standard deviation using the relationship 6Q.D.=5M.D.=4S.D.6Q.D.=5M.D.=4S.D., providing a quick method to approximate other dispersion measures.<\/p>\n\n\n\n<h2 id=\"conclusion\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span><strong>Conclusion<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Quartile deviation is a valuable statistical tool for <a href=\"https:\/\/pickl.ai\/blog\/advanced-excel-chart-types\/\">analysing data<\/a> dispersion, especially when dealing with datasets that contain outliers. By focusing on the middle range of data, it offers insights into how spread out the central portion of the data is. Whether you&#8217;re working with ungrouped or grouped data, quartile deviation provides a straightforward method to quantify dispersion.<\/p>\n\n\n\n<h2 id=\"frequently-asked-questions\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions\"><\/span><strong>Frequently Asked Questions<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3 id=\"what-is-quartile-deviation-used-for\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_Is_Quartile_Deviation_Used_For\"><\/span><strong>What Is Quartile Deviation Used For?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>It is used to measure the dispersion of data, focusing on the middle 50% to provide insights into data spread without being influenced by outliers.<\/p>\n\n\n\n<h3 id=\"how-does-quartile-deviation-differ-from-standard-deviation\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"How_Does_Quartile_Deviation_Differ_from_Standard_Deviation\"><\/span><strong>How Does Quartile Deviation Differ from Standard Deviation?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Unlike standard deviation, quartile deviation is less affected by outliers, making it more suitable for skewed distributions.<\/p>\n\n\n\n<h3 id=\"what-are-the-advantages-of-using-quartile-deviation\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_are_the_Advantages_of_Using_Quartile_Deviation\"><\/span><strong>What are the Advantages of Using Quartile Deviation?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>It is robust to outliers and provides an easy-to-understand measure of data spread, making it ideal for datasets with extreme values.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"Robust measure of data dispersion, resistant to outliers and skewed distributions.\n","protected":false},"author":19,"featured_media":20402,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[2346],"tags":[3835,3836],"ppma_author":[2186,2184],"class_list":{"0":"post-20401","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-statistics","8":"tag-quartile-deviation","9":"tag-quartile-deviation-in-statistics"},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.3 (Yoast SEO v27.3) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>What is Quartile Deviation? 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