You could imagine a line that looks something like this. It would fit the data quite well. And the reason why you might wanna do this versus trying to fit an exponential is because we've already developed so many tools around linear regression and hypothesis testing around the slope and confidence intervals. And so this might be the direction you wanna go at. And what's neat is once you fit a linear regression, it's not difficult to mathematically unwind from your linear model back to an exponential one. So the big takeaway here is is that the tools of linear regression can be useful even when the underlying relationship between x and y are nonlinear. And the way that we do that is by transforming the data.