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Sum of square Residuals
The sum of square residuals, denoted SSres, is a measure of fit for a model. It works like this:
Take the difference between the actual values yi and the values predicted by the model, which we call y^i.
Square each of those differences
Add them all up to find SSres
In short, SSres is how far off the model is at each point, squared, and added for all the points. Visually, SSres is the sum of the areas of these squares:
In IB exams, you need to know how to find it from a table:
Adding these all up gives
You can use your calculator to do this more quickly using list and summation features.
Sum of square Residuals
The sum of square residuals, denoted SSres, is a measure of fit for a model. It works like this:
Take the difference between the actual values yi and the values predicted by the model, which we call y^i.
Square each of those differences
Add them all up to find SSres
In short, SSres is how far off the model is at each point, squared, and added for all the points. Visually, SSres is the sum of the areas of these squares:
In IB exams, you need to know how to find it from a table:
Adding these all up gives
You can use your calculator to do this more quickly using list and summation features.