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Linear regression attempts to model the relationship between two variables by fitting a linear equation to observed data.
One variable is considered to be an explanatory variable, and the other is considered to be a dependent variable.
For example, a modeler might want to relate the weights of individuals to their heights using a linear regression model.
Use the Khan Academy link to learn about linear regression.
Practice
Practice
Use the Geogebra activity to estimate the regression line for the given data.
Click "Residuals" to see the residuals generated by your estimate. Remember, the line of regression is where the sum of the residuals is zero.
Have a play with the data set by manually changing the value of selected data points by clicking and dragging them.
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