If one shirt is sold for $15.50, the amount of shirts you'd be able to buy with $139.50 is 9.
Multiply 9 by 3 and you get your answer: 27 Shirts
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>
Let's write it down:
<span>"60 is 75% of s" means:
60=75%*s
75% is

, (percent just means "out of 100" so we just divide it by 100) so we can also write:
60=</span><span>

s
now, let's multiply both sides by 4:
240=3s
and divide by 3:
80=s
So we have the result that the original value, s, is 80!
</span>
Answer:
.152
Step-by-step explanation:
only 14 but might be right