least squares for fitting experimetal data

I am an undergrad in chemistry and do not have a strong background in coding. Anyways my question is I have to to make a lot of linear fits form experimental data and I was wondering if there is an easy way to do this using least squares (which I do understand. At least more than coding) I am trying to avoid using the basic fit option to enhance my repertoire.

Answer 1

[Star Strider]

There are three straightforward ways to do linear least-squares fitting in MATLAB:

1. The mldivide,\ operator (or function),

2. The polyfit function,

3. The fminsearch function (although you have to code the objective function for it)

Admittedly, fminsearch is serious overkill for a linear problem, but I want to be certain I cover all the options. It is quite useful for small nonlinear problems (fewer than about 6 parameters) that you will eventually encounter in Chemistry.

EDIT — There are a number of other options in the Statistics and Machine Learning Toolbox, but assuming you’re interested in only the functions available in core MATLAB, they’re all I covered here.