Covariance, Correlation, R-Squared | by Deepak Khandelwal | The Startup | Medium

This article is dedicated to the explanation of the three closely related but still different concepts namely — covariance, correlation and R-Squared. This also describes about the interpretation of the three. What is variance? Random variables, by definition, can take different values. The range of values a random variable takes and the variation among them is determined by the distribution of that random variable. Next, the expected value (aka mean, average, expectation) of a random variable tells us what value we can expect from a random variable on an average. For example, throwing a six sided die is a random variable (D) which can take the following values — [1, 2, 3, 4, 5, 6]. The probability of D taking any of the six values is 1/6 for all the values. Hence D follows a uniform distribution. The expected value of D, denoted as E[D], is 3.5. But what we are interested in is what maximum and minimum values it can take and what is the variation from the expected value. This is defin

This article is dedicated to the explanation of the three closely related but still different concepts namely — covariance, correlation and R-Squared. This also describes about the interpretation of the three. What is variance? Random variables, by definition, can take different values. The range of values a random variable takes and the variation among them is determined by the distribution of that random variable. Next, the expected value (aka mean, average, expectation) of a random variable tells us what value we can expect from a random variable on an average. For example, throwing a six s