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

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:

I used h to denote hours. Our prediction of temperature for the sixth hour would be:

Here is a link to the spreadsheet  (https://docs.google.com/spreadsheets/d/17awPz5U8Kr-ZnAAtastV-bnvoKG5zZyL3rRFC9JqVjM/edit?usp=sharing)

Do you need with the x value for the minimum? its always between the two intercepts for a parabola