Question 1108180
i believe the r^2 will tell you that.


r^2 tells you how well the model fits your data.


if r^2 is high, then you have a good fit.


if r^s is not so high, then you don't have a good fit.


if you're not sure, you would model using the different types of modeling techniques and then look at the r^2 for each.


the better fitting model would be the one with the higher r^2.


i'm not an expert, but that's what i would do if i was in doubt as to which model gave me the best fit for the data.


here's a more complex method taken from the web which i don't understand fully.


<a href = "http://statisticsbyjim.com/regression/model-specification-variable-selection/" target = "_blank">http://statisticsbyjim.com/regression/model-specification-variable-selection/</a>


here's another one from the web.


<a href= "https://www.theanalysisfactor.com/assessing-the-fit-of-regression-models/" target = "_blank">https://www.theanalysisfactor.com/assessing-the-fit-of-regression-models/</a>


lots more on the web.
i did a search for "how to determine the type of regression model to use"
and some of the options are the ones shown above.


it appears that r^2 is a good test, but it's not quite so simple as it might seem at first and other types of test might be required as well.