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>
Answer:
Step-by-step explanation:
cos(c)= x/ac
ac = cos32/9.4
ac =11.08
Answer:
g(x)=3
Step-by-step explanation:
Let's find the answer.
W(f,g)=3e^x which can be written as:
W(f,g)=(3)*(e^x), notice that:
(e^x)=f(x) so:
W(f,g)=3*f(x), establishing:
W(f,g)=g(x)*f(x) then:
g(x)=3
In conclusion, g(x)=3.
<span>A linear equation is any equation used to define a line. </span>
Answer:
Pamela bought a piece of meat using 3/8 of that piece to make stew and there were 3/4 kg left over how much did the piece of meat he ate originally weigh?
Step-by-step explanation:
I searched it up. hopefully it helps