How to fit non-linear equations in excel using solver

Tutorial of how to fit non-linear curves in excel using solver. This tool lets you fit custom equations to your data. For example in this example we fit data to a modified version of the Avrami equation.

Thanks to Ozkar and Finke for their data and if you want to learn how to grab data from papers using WebPlotDigitizer, check out my video tutorial.

[matthulvey]

Very helpful. One thing to note. The real reason we square the residuals is to ensure that that we are not minimizing the sum with positives and negatives. Being on either side of the fit is an error, but if left unchecked a residual of 0.1 and -0.1 would equate to zero when in fact they should be agnostic to which side the error occurred and sum to 0.2 . To fix that we square the values and everything is positive, thus finding the "least squares" gives us the best fit. I don't know if that is what you were implying in the video, but I did not hear that called out.

[carloscantu]

Great explanation. Straight to the point and without missing any necessary details. I'll look at your videos for future questions.

[feynstein]

I'm here from July 2023 and I'd like to say that this is EXACTLY how neural networks are trained. I watched Andrej Karpathy's full coding of ChatGPT and this is exactly what he did there. We have a certain expected output from the network. But the real output is different. We measure the difference i.e. residual i.e. error and work on minimizing that. That's literally all there is to it. The code is just there to make this process easier and find each parameter for billions of neurons.

[michealcairns]

As a researcher myself investigating heterogeneous behavior, this short tutorial was extremely helpful. Brilliant explanation, Subscribed!

[IrishJade]

I have watched so many videos on how to do this and this is the first one that actually made sense and where I actually understood what components went where. Amazing! Thank you so much!

[chadmace]

all these years I've always used Matlab or Python... Often find myself in Excel... this will work well. Thank you!

[meganmcgee]

This is amazingly helpful! I watched numerous videos trying to do logistic regression fitting and this is the only one that helped me!

[mjmeternal]

You made it very easy. In order to fit a model, bring any equation and very the parameters then go to Solver to minimise the sum of the squared Residuals (SSR) and this gives the best values for parameters.

[potatofries]

bruh this explanation goes hard it was so clear and concise, I've tried to read how to use solver from other sources but they were always convoluted and not too useful. this video in contrast was good and efficient thank you!

[timr]

You explained it in 6 minutes better than my docent in 2 90min sessions, thank you so much!!

[architkulkarni]

Hi Taylor, thank you for such precise explanation. I want to know how can we find uncertainty in fitting parameters and eventually the goodness of the fit?

[ruslanakbar]

Hey, Taylor! Just wanted to thank for your all work, from material science to statistics!!!

[charlierettner]

Great job leading us through this so smoothly. I suspect that most people coming here are like me and know what they want Excel to do but had no idea it could do it. It took me about 60 seconds to learn how to use solver from your video, as opposed to never on my own. Thanks!

[georgehellas]

Thanks, you literally saved me trying to interpolate a sine wave to data that looked like a sine wave. Again

[kurry]

Dude, helped me out so much, thought I had to redo all of my measurements for a uni project. Very well done!

[dr.ajaysujan]

Explain everything in very easy manner... Nice job

[saidfigueredo]

My english listening is very very bad, but it was no a problem for I reproduce your procedure, excellent, thank you so much bro

[esraelsamuel]

Thank You, Taylor. I was trying to fit using MATLAB. However, your video is awesome

[bowenqin]

a good solution to find the equations for solving "the area of hysteresis" problem. Thank you so much

[prasannareddy]

i LOVE THE VIDEO, I ASKED MANY PEOPLE ABOUT IT, BUT NONE COULD EXPLAIN ME BETTER. Thank you