1.0KaLabshttps://karthicklakshmanan.comkarthickhttps://karthicklakshmanan.com/index.php/author/karthick/rich600338<blockquote class="wp-embedded-content" data-secret="vfOwXPsfw6"><a href="https://karthicklakshmanan.com/index.php/knowledge-base/univariate-analysis/">Univariate analysis</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://karthicklakshmanan.com/index.php/knowledge-base/univariate-analysis/embed/#?secret=vfOwXPsfw6" width="600" height="338" title="“Univariate analysis” — KaLabs" data-secret="vfOwXPsfw6" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script> /*! This file is auto-generated */ !function(d,l){"use strict";l.querySelector&&d.addEventListener&&"undefined"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!/[^a-zA-Z0-9]/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),o=l.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),c=new RegExp("^https?:$","i"),i=0;i<o.length;i++)o[i].style.display="none";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute("style"),"height"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):"link"===t.message&&(r=new URL(s.getAttribute("src")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener("message",d.wp.receiveEmbedMessage,!1),l.addEventListener("DOMContentLoaded",function(){for(var e,t,s=l.querySelectorAll("iframe.wp-embedded-content"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute("data-secret"))||(t=Math.random().toString(36).substring(2,12),e.src+="#?secret="+t,e.setAttribute("data-secret",t)),e.contentWindow.postMessage({message:"ready",secret:t},"*")},!1)))}(window,document); </script> Univariate analysis is a statistical technique used to analyze a single variable in isolation. It focuses on understanding the distribution and characteristics of a single variable without considering its relationship with other variables. Univariate analysis helps in summarizing the main features of the variable, identifying patterns, detecting outliers, and making preliminary assessments about the data. Here are some common methods used in univariate analysis: Univariate analysis provides valuable insights into the characteristics of individual variables and serves as a foundation for further analysis, such as bivariate and multivariate analysis. It helps in understanding the data’s structure, identifying potential patterns or trends, and detecting any anomalies or irregularities.