I used to work with MATLAB, and for the question I raised I can use p = polyfit(x,y,1) to estimate the best fit line for the scatter data in a plate. I was wondering which r
I would suggest coding it from scratch. It is a very simple implementation in C++. You can code up both the intercept and gradient for least-squares fit (the same method as polyfit) from your data directly from the formulas here
http://en.wikipedia.org/wiki/Simple_linear_regression#Fitting_the_regression_line
These are closed form formulas that you can easily evaluate yourself using loops. If you were using higher degree fits then I would suggest a matrix library or more sophisticated algorithms but for simple linear regression as you describe above this is all you need. Matrices and linear algebra routines would be overkill for such a problem (in my opinion).