I have two questions:
Which regression should I choose and why?
Based on the R squared value, exponential regression seems to be a better fit. But I am not really sure, if I should just go with it because it has a higher R squared value?
How do I validate it?
Lets say I decided to go with the linear regression (despite its smaller R squared value.) The only process I am following is to manually calculate the residuals and fit a histogram to check if they are normally distributed. And apparently they are OK in this case.
However, my concern is that some values (red circled ones) don't seem to be fitting well since their error is too high. But still, I suspect that they do not undermine R squared value, because are symmetric to each other. So it will probably add a bias?
So what is to best way to validate my choice of regression against such cases (besides high R squared value and normality check.) And are there other biases that I should look for?