![]() In the scatterplot, we can see a positive relationship exists between study time and test scores. Imagine we have a list of people’s study hours and test scores. You’ll see a lot of sums in the least squares line formula section!įor a given dataset, the least squares regression line produces the smallest SSE compared to all other possible lines-hence, “least squares”! Least Squares Regression Line Example In this case, it’s the sum of all residuals squared. Statisticians refer to squared residuals as squared errors and their total as the sum of squared errors (SSE), shown below mathematically. In this manner, the process can add them up without canceling each other. ![]() ![]() Instead, least squares regression takes those residuals and squares them, so they’re always positive. Unfortunately, you can’t just sum the residuals to represent the total error because the positive and negative values will cancel each other out even when they tend to be relatively large. ![]()
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