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 (
<span>https://docs.google.com/spreadsheets/d/17awPz5U8Kr-ZnAAtastV-bnvoKG5zZyL3rRFC9JqVjM/edit?usp=sharing)</span>
x = 1 because -7(3x + 4) must be -49 so 3x + 4 must me 7 so x = 1
a.
In order to find the common ratio, we just need to divide a term by the term that comes before it.
So using the terms 20 and -5, we have:

b.
The recursive rule can be found with the formula:

Where an is the nth term and q is the ratio. So we have:

c.
The explicit rule can be written as:

Where an is the nth term, a1 is the first term and q is the ratio. So:
The answer is 10...............