Difference Between Correlation and Regression
Correlation and regression are tightly related, but they serve slightly different purposes. A regression predicts and describes the relationship between two variables whereas a correlation only identifies if there was a relationship between them in the past.
Develop an original response describing a scenario where you might need to use regression instead of correlation. How could a regression model serve your purpose?
What Is The Difference Between Correlation and Regression?
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Although not mutually exclusive, regression and correlations are different approaches. Regression is a technique of forecasting future happenings between the target (dependent) and one or more predictor (independent) variables (Gunst & Mason, 2018). On the other hand, correlation measures the monotonic relationship between two variables. A monotonic association between two variables can be described as one whereby an increase in one variable increases the other variable’s value. It also represents a relationship where one value decreases as the other increases (Schober et al., 2018). Considering a scenario where regression is applied instead of correlation, I would use the former to forecast the association between careless driving and the total number of road accidents caused by such drivers. Compared to correlation analysis, which quantifies the extent to