Learn Data Science using Python

Another post starts with you beautiful people! I hope you have learnt something from my previous post about computing the ECDF, plotting the ECDF, comparison of ECDFs, mean, percentile and covariance. If you haven't seen the post then please visit here  statistically thinking as a data scientist-1 In this post we will learn following topics- Computing the Pearson correlation coefficient Bernoulli trials Binomial distribution Poisson distributions Normal PDF/CDF Computing the Pearson correlation coefficient - The Pearson correlation coefficient, also called the Pearson r , is often easier to interpret than the covariance. I must suggest you to read more about this here-  A Must Read about Pearson Correlation Coefficient It is computed using the np.corrcoef() function. Like np.cov(), it takes two arrays as arguments and returns a 2D array. Entries [0,0] and [1,1] are necessarily equal to 1 ( can you think about why? ), and the value we are after is entry [...