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A positive value of covariance indicates that two random variables tend to vary in the same direction, whereas a negative value suggests that these variables vary in opposite directions.

This article will also be a good read for anyone who wants to refresh his/her statistical knowledge.Ĭovariance can take negative or positive values as well as value 0. If you have no prior Statistical knowledge and you want to identify and learn the essential statistical concepts from the scratch, to prepare for your job interviews, then this article is for you. In this article, I will cover the following Statistics topics for data science and data analytics: - Random variables - Probability distribution functions (PDFs) - Mean, Variance, Standard Deviation - Covariance and Correlation - Bayes Theorem - Linear Regression and Ordinary Least Squares (OLS) - Gauss-Markov Theorem - Parameter properties (Bias, Consistency, Efficiency) - Confidence intervals - Hypothesis testing - Statistical significance - Type I & Type II Errors - Statistical tests (Student's t-test, F-test) - p-value and its limitations - Inferential Statistics - Central Limit Theorem & Law of Large Numbers - Dimensionality reduction techniques (PCA, FA) Knowing the fundamentals of these two important subjects will allow you to think critically, and be creative when using the data to solve business problems and make data-driven decisions. Both Statistics and Mathematics love facts and hate guesses. Statistics provides tools and methods to find structure and to give deeper data insights. The importance of statistics in data science and data analytics cannot be underestimated. “Statistics is the grammar of science.” Karl Pearson When you are getting started with your journey in Data Science or Data Analytics, having statistical knowledge will help you to better leverage data insights. As Karl Pearson, a British mathematician has once stated, Statistics is the grammar of science and this holds especially for Computer and Information Sciences, Physical Science, and Biological Science.