Midsegment = 1/2(base1 + base2)
EF = 1/2(AB + CD)
EF = 1/2(20 + 12)
EF = 1/2(32)
EF = 16
Answer
EF = 16
This graph is growing exponentially, 0.5 more each time at every point
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>
The expression you want to simplify is 0-(x-y).
0-(x-y)
=-(x-y)
=-x+y
You just have to treat the negative sign in front of (x-y) as a -1 and distribute it to both x and -y.