Least-Square Linear Regression of Data Using C++ | Code Samurai

Least-Square Linear Regression of Data Using C++ | Code Samurai

Least-Square Linear Regression of Data Using C++

Question: implement the least-square method to determine the linear function that best fits the data. This method also needs to find the coefficient of determination (R^2) and standard error of estimation (E). Input to this method is a collection of data points (x, y) and the collection's size, a.k.a. number of data points.

Solution: the answer is straight forward. We basically just have to apply the statistics formulas for finding the least-square linear function to the data. If you are not familiar with the formulas and where they come from here is the link for you. Now, let's take a look at the implementation below:

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