The regression analysis evaluates the amount of relationship that exists
between the variables in the analysis.
- The regression equation is;

- The prediction is worthwhile because it gives an idea of the observed Crash Fatality Rate and it is therefore approximately correct.
Reasons:
First part;
The given data is presented as follows;
![\begin{tabular}{|cc|c|}Lemon Imports (x) &&Crash Fatality Rate\\232&&16\\268&&15.7\\361&&15.4\\472&&15.5\\535&&15\end{array}\right]](https://tex.z-dn.net/?f=%5Cbegin%7Btabular%7D%7B%7Ccc%7Cc%7C%7DLemon%20Imports%20%28x%29%20%26%26Crash%20Fatality%20Rate%5C%5C232%26%2616%5C%5C268%26%2615.7%5C%5C361%26%2615.4%5C%5C472%26%2615.5%5C%5C535%26%2615%5Cend%7Barray%7D%5Cright%5D)
The least squares regression equation is; 
Where;

= The mean crash fatality = 15.52
= The mean lemon import = 373.6
Therefore;

c =
- b·
= 15.52 - (-0.00255)×373.6 = 16.47268
Therefore;
- The regression equation is

Second part;
When the imports is 425 metric tons of lemon, we have;
= -0.00255 × 425 + 16.47268 = 15.38893 ≈ 15.4
Therefore;
When the import is 425 metric tons, the Crash Fatality Rate ≈ 15.4
Given that the predicted value is between the values for 268 and 535, we
have that the prediction is approximately correct or worthwhile
<u>The prediction is worthwhile</u>
Learn more about regression equation here:
brainly.com/question/5586207