Question

The data set represents a progression of hourly temperature measurements.Use the regression equation to predict the temperature during the sixth hour. x 0 1 2 3 4 5 y 20 16 10 0 -7 -20

Answer 1

I will attach google sheet that I used to find regression equation.
We can see that linear fit does work, but the polynomial fit is much better.
We can see that R squared for polynomial fit is higher than R squared for the linear fit. This tells us that polynomials fit approximates our dataset better.
This is the polynomial fit equation:
$T(h)=20.2-3.6h-0.875h^2$
I used h to denote hours. Our prediction of temperature for the sixth hour would be:
$T(6)=20.2-3.6(6)-0.875(6)^2=-32.9$
Here is a link to the spreadsheet  (https://docs.google.com/spreadsheets/d/17awPz5U8Kr-ZnAAtastV-bnvoKG5zZyL3rRFC9JqVjM/edit?usp=sharing)

Answer 2

Answer:

the answer is C: y = -0.875x^2 - 3.956x + 20.179

Step-by-step explanation: