Answer:
I Know the answer because I am in k12 too.
The answer is 37.5%
Step-by-step explanation:
$80 - $50 = $30
$30 * 100 / $ 80 = 37.5%
answer: 37.5% of decrease.
<h2>7x + 19 = 208</h2><h2>11x - 89 = 208</h2><h2>--------------------------------------</h2>
<u>Step-by-step explanation:</u>
let third angle be x
60° + 60° + x = 180° (Δ sum property)
x = 60°
so, this is a equilateral triangle (all Δ equal)
<h2>-----------------------------------------</h2>
in equilateral triangle --> all sides are equal
so, therefore =>>
7x + 19 = 11x - 89
19 + 89 = 11x - 7x
108 = 4x
108 ÷ 4 = x
27 = x
<h3>x = 27</h3><h2>-----------------------------------------</h2>
so variable
1.) 7x + 19
= 7(27) + 19
= 189 + 19
= 208
2.) 11x - 89
= 11(27) - 89
= 297 - 89
= 208
Answer:
c) 18 units
d) 1 second
Step-by-step explanation:
h = -16t² - 4t + 20
c) t = 0.25
h = -16(0.25)² - 4(0.25) + 20
h = 18
d) -16t² - 4t + 20 = 0
4t² + t - 5 = 0
4t² + 5t - 4t - 5 = 0
t(4t + 5) - (4t + 5) = 9
(4t + 5)(t - 1) = 0
t = -1.25, 1
t = 1 second
583939485933094939392....../
Answer:
Yes
Step-by-step explanation:
The central limit theorem says that If a random variable X from a population has mean u and finite variance σ² , then the sampling distribution of the sample mean X~ approaches a normal distribution with mean u and variance σ²/n as the sample size n approaches infinity.
It is interesting to note that we have neither assumed that the distribution of X is continuous nor we have said anything about the shape of the distribution , whereas the limiting distribution of X is continuous and normal. Thus the distribution of the sample means regardless of the shape of the population having a finite variance , is approximately normal with mean u and variance σ²/n .
Therefore
(standard deviation/ √sample size)²= variance / n
2/ √20
= 2/4.472
=0.44721
The sampling distribution of X` is therefore approximately normal with mean ux=u and σx =σ/n
