From the course: Probability Foundations for Data Science

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Correlation

Correlation

From the course: Probability Foundations for Data Science

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Correlation

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- [Instructor] Let's put variance and covariance together to explore correlation. Correlation is similar to covariance where it also measures the relationship of how two random variables change together. Correlation tends to focus on how these two random variables move together regarding their direction and strength. For two random variables, X and Y, their correlation is defined by the following equation. This is where you divide the covariance of X and Y by the standard deviation of X multiplied by the standard deviation of Y. This is the same general equation for discrete and continuous random variables, but the specifics of how to get the covariance and standard deviations of these follow the equations previously shared. The equation is equal to what is called the correlation coefficient, and it is often denoted with a P or an R. The correlation coefficient P ranges between the values of negative one to one, and you can interpret the correlation as so. A P value of one indicates a…

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