May be there is an operator missing in the first function, h(x). I will solve this in two ways, 1) as if the h(x) = 5x and 2) as if h(x) = 5 + x
1) If h(x) = 5x and k(x) = 1/x
Then (k o h) (x) = k ( h(x) ) = k(5x) = 1/(5x)
2) If h(x) = 5 + x and k (x) = 1/x
Then (k o h)(x) =k ( h(x) ) = k (5+x) = 1 / [5 + x]
Answer: Adiya’s method is not correct. To form a perfect square trinomial, the constant must be isolated on one side of the equation. Also, the coefficient of the term with an exponent of 1 on the variable is used to find the constant in the perfect square trinomial. Adiya should first get the 20x term on the same side of the equation as x2. Then she would divide 20 by 2, square it, and add 100 to both sides.
Answer:
h=48
Step-by-step explanation:
You should create an even proportion. So you could do seconds over heartbeats or the other way around. I decided to do the other way around. Since yu want to see h in m minutes and in a minute there are 60 seconds, I did 8/10 = h/60. Instead of cross multiplying, I saw that 10 times 6 is 60 so 8 x 6=h. 8 x 6 = 48 so h=48.
Answer:<em><u> 
π
. </u></em>
Given:
Using Gauss's Law = ∫∫s E ·dS
= ∫∫∫ div E dV,
⇒ Divergence (Gauss') Theorem
= ∫∫∫ (1+1+6) dV
= 8×(volume of the hemisphere, radius "a")
= 8× (
)(4/3)π
<em><u>= π . </u></em>
According to the statement above, The Hamden board of education called every <span>tenth person on the registration list. So let's analyze each case:
</span><span>The sample is not randomly chosen (FALSE)
Given that the statement doesn't tell us anything about the way they choose the sample, it is reasonable to conclude that this is a </span>randomly chosen. They called every tenth person on the registration list until the number of people was 40.
The sample should be larger to give more reliable information (TRUE)
You did not have to use mathematics to determine that you would need more information to get a conclusion. You must increase the sample, that is, the sample must be larger to give a reliable information.
The sample size is too large to make inferences (False)
This is explained in the previous item. If the sample should be lager is because the size is not too large.
The sample size is too small to represent the population (TRUE
This is true because 40 voters represent barely 0.5% of the entire list. This list has 7300 voters, so getting the conclusion from this sample doesn't provide with a strong conclusion.
<span>The sample size is too small and will show larger variation. (FALSE)
Although the sample size is too small, the sample size not necessarily will show variation. In fact, it is possible that it does not show any variation and most of the people feel well about building a new media center for the middle school but it doesn't mean that the whole community does.
The sample is invalid because it randomly chooses voters. (FALSE)
It is false because in probability studies the sample is chosen randomly, so you get conclusions about the whole population always taking samples that represent the population as a whole.
The sample size is too small and can lead to false inferences (TRUE)
You can get false conclusions given that the sample size is too small. <span>It's important to note that the sample size supports the conclusion of the study, so the sample must increase to have a reliable study.
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