Answer:
The equation is;
4y = 7x + 2
Step-by-step explanation:
The general equation of a straight line is;
y = mx + b
where m is the slope and b is the y-intercept
m = (y2-y1)/(x2-x1)
(x1,y1) = (2,3)
(x2,y2) = (-2,-4)
m = (-4-3)/(-2-2) = -7/-4 = 7/4
So we have the equation as;
y = 7x/4 + b
To
get the value of b, we will substitute any of the points (let us use 2,3)
We simply substitute 2 for x and 3 for y
We have this as:
3= 7(2)/4 + b
3 = 7/2 + b
b = 3-7/2 = -1/2
So we have the equation as;
y = 7x/4 + 1/2
multiply through by 4
4y = 7x + 2
Answer
a. True
Step-by-step explanation:
Based on this survey we estimate that about 
of the college students smokes. And a 
confidence interval is ![[15.1\% ; 21.6\%]](https://tex.z-dn.net/?f=%5B15.1%5C%25%20%3B%2021.6%5C%25%5D)
. So we know that 
our estimative for the smoking rate is in the confidence interval with certainty. We also know the estimative for the smoking rate in the general population is 
. So we can write the two possible hypothesis:
Smoking rate is equal to .
Smoking rate is not equal to .
We will reject the null hypothesis 
if the estimate doesn't fall into the confidence interval for the college students smoking rate.
Since this condition holds we reject the null hypothesis. So with certainty we say that the smoking rate for the general population is different than the smoking rate for the college students.
Answer:
<h3>
It's about 365 cm²</h3>
Step-by-step explanation:
2×πr² + 2πr×h =
= 2×π×4² + 2π×4×10.5 =
= 32π + 84π =
= 116π ≈
≈ 364.42 cm²
-19 is the answer ////////////////// sorry i needed more charecters to answer
Answer: Choice B
There is not convincing evidence because the interval contains 0.
========================================================
Explanation:
The confidence interval is (-0.29, 0.09)
This is the same as writing -0.29 < p1-p1 < 0.09
The thing we're trying to estimate (p1-p2) is between -0.29 and 0.09
Because 0 is in this interval, it is possible that p1-p1 = 0 which leads to p1 = p2.
Therefore, it is possible that the population proportions are the same.
The question asks " is there convincing evidence of a difference in the true proportions", so the answer to this is "no, there isn't convincing evidence". We would need both endpoints of the confidence interval to either be positive together, or be negative together, for us to have convincing evidence that the population proportions are different.
