Answer
$β_0=-0.31$
$β_1=0.2119$
$ŷ =16.68~chirps~per~second$
Work Step by Step
In MINITAB, enter the Temperature values in C1 and in C2 enter the Chirps per Second values.
Select Stats -> Regression -> Regression -> Fit Regression Model
Enter C2 in "Responses" and C1 in "Continuous Predictors"
The least-squares regression line ($ŷ =b_1x+b_0$) will be shown in "Regression Equation", where C2 is ŷ (Chirps per Second) and C1 is x (Temperature)
$ŷ =0.2119x-0.31$
That is:
$b_0=-0.31$ and $b_1=0.2119$
$b_0$ is the estimate for $β_0$ and $b_1$ is the estimate for $β_1$.
When the temperature is 80.2 °F, that is, $x=80.2$:
$ŷ =0.2119\times80.2-0.31=16.68$
