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 find the slope for line t first.
We can use the given points 2,6 and 10,1 to find the slope using the slope formula.

1 - 6 / 10 - 2
-5/8
The slope is -5/8.
Because we know the slope of this line, we can find the slope of the next line instantly, as they are perpendicular.
When a slope is perpendicular to another, it is equal to the negative reciprocal.
Negative reciprocal of -5/8 = 8/5
<h3>The slope of line u is 8/5</h3>
Answer:
15
Step-by-step explanation:
30 pounds divided by 2
Answer:
4000
Step-by-step explanation:
let the marked price of the cycle be x
then x · (100% + 5% + 12%) = 4680
x =
= 4000
Answer:
x≥10 or x∈[10, ∞)
Step-by-step explanation:
The graph we are given is h(x) = |x-10|+6, which has the shape of a V. The vertex is at (10, 6), so to the right of the vertex, the graph is increasing.
Therefore, the graph increases during the interval x≥10 or x∈[10, ∞).