Statistics 101- Measures of Central Tendency
<p>The first step into a data project is understanding the distribution of the numerical columns. Hence in python we have the <code>df.describe()</code> method which gives the major statistical results of the numerical columns for the given data set. The result consists of the <strong>mean</strong>, the <strong>median</strong>, the upper and lower <strong>quartiles</strong>, and the <strong>standard deviation </strong>of the respective columns.</p>
<p>This post is a going to be a theoretical refresh on the concepts of the measures of central tendency. So, why is it called <em>central</em> tendency? Let’s take a very easy example of a class of 10 students and their respective heights (in centimeters). For the given age, there will an average height and there will be some who are taller or shorter than the said average. The data will have some central values which are representative of the sample, and can potentially be extrapolated to the larger population.</p>
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