Parametric and Non-Parametric Correlation in Data Science!

This article was published as a part of the Data Science Blogathon. Hey, are you working on a data science project, solving a problem statement related to data science, or experimenting with a statistical test to make further decisions and handling the most repeatedly cited statistical term, 'correlation'? Willing to correctly interpret these statistical terms (covariance, parametric and non-parametric correlation)? Which method will outperform or underperform in your problem statement in a specific scenario (i.e., sensitive to outliers, type of distribution, etc.)? Working on sample data and willing to know the probable error of the coefficient?