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>
Step-by-step explanation:
answer in photos
here m is intercept
Answer:
The answer is: 1, 2, and 6
Step-by-step explanation:
Answer:
0.10
Step-by-step explanation:
0.10 = 10/100 or 10%
Multiply 400*0.10 to get 10% of 400.
Answer:
its the the second one not the first one