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>
R - 3 < 5
r < 5 + 3
r < 8 Answer
Answer:
1. 74 because 8(10) - 6
2.4(4) - 5(3) = 1
3. 7(3)+8(4) * 2 = 106
4. A
5.a
6. 20.5
7.26
8.a
9.a
10a
Step-by-step explanation:
Answer:
The total cost will be $40 plus $1.50 per square foot of carpet or $40+$1.50x