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Simple Linear Regression: It's used when you want to understand the relationship between two variables, one as the predictor (independent variable) and the other as the response (dependent variable). For example, assessing the relationship between the number of hours studied and exam scores.
Multiple Linear Regression: This method allows you to examine the relationship between the response variable and multiple predictor variables. It's ideal for situations where the outcome depends on more than one factor. For example, predicting a person's income based on their education, years of experience, and age.
