Using Exponential Regression to Fit a Model to Data

In 2007, a university study was published investigating the crash risk of alcohol impaired driving. Data from 2,871 crashes were used to measure the association of a person’s blood alcohol level (BAC) with the risk of being in an accident. The table shows results from the study. The relative risk is a measure of how many times more likely a person is to crash. So, for example, a person with a BAC of 0.09 is 3.54 times as likely to crash as a person who has not been drinking alcohol.

$$\begin{array}{ccccccc}\text{BAC}& \text{0}& \text{0.01}& \text{0.03}& \text{0.05}& \text{0.07}& \text{0.09}\\ \text{Relative Risk of Crashing}& \text{1}& \text{1.03}& \text{1.06}& \text{1.38}& \text{2.09}& \text{3.54}\\ \text{BAC}& \text{0.11}& \text{0.13}& \text{0.15}& \text{0.17}& \text{0.19}& \text{0.21}\\ \text{Relative Risk of Crashing}& \text{6.41}& \text{12.6}& \text{22.1}& \text{39.05}& \text{65.32}& \text{99.78}\end{array}$$

(a) Let $x$ represent the BAC level, and let $y$ represent the corresponding relative risk. Use exponential regression to fit a model to these data.
(b) After 6 drinks, a person weighing 160 pounds will have a BAC of about $\mathrm{0.16.}$ How many times more likely is a person with this weight to crash if they drive after having a 6-pack of beer? Round to the nearest hundredth.

Its source prints no answer for this problem, so there's nothing to check against.

OpenStax, Algebra and Trigonometry 2e · §6.8 Fitting Exponential Models to Data · Example 3