:)
The formula of the future value of annuity ordinary is
Fv=pmt [(1+r/k)^(kn)-1)÷(r/n)]
So we need to solve for pmt
Pmt=fv÷[(1+r/k)^(kn)-1)÷(r/n)]
Pmt=200,000÷(((1+0.10÷4)^(4×5)
−1)÷(0.10÷4))=7,829.43...answer
Hope it helps
Each side of the model of 413s is rectangular shaped.
So, by this statement we got to know that the model is in cuboid shape.
Hence, its volume will be (length×width×height) cubic feet.
Answer:
Step-by-step explanation:
we know that
The equation of the line into point slope form is equal to
In this problem we have
substitute the given values

therefore
y minus StartFraction one-third EndFraction equals StartFraction 3 Over 4 EndFraction left-parenthesis x minus 4 right-parenthesis.(x – 4)
Answer:
760 attendees
Step-by-step explanation:
40% of the attendees is 304. That means you can add 304 to 304 (304 x 2) to get 608. To get the last 20%, divide 304 by 2, because 40(%) divided by 2 is 20(%). The answer to that is 152. Now, add it all up. 608 + 152 = 760.
In conclusion, there were 760 attendees at the carnival.
Answer:
There is no enough evidence to claim that there is a difference between the two population proportions.
Step-by-step explanation:
We have to perform an hypothesis testing for a difference between two population proportions.
The null hypothesis will state that both proportions are the same, and the alternative hypothesis will state that they differ. This would be than a two-side hypothesis test.
We can write this as:

The significance level for this test is 0.05.
The sample of city residents with school-age children has a sample size n1=230 and a sample proportion p1=0.41

The sample of city residents without school-age children has a sample size n2=341 and a sample proportion p2=0.51

The weighted p, needed to calculate the standard error, is the weighted average of both sample proportions:

The standard error of the difference of proportions can now be calculated as:

The test statistic z is:

The P-value for this two side test and this value of the z-statistic is:

The P-value is bigger than the significance level, so the effect is not significant. The null hypothesis failed to be rejected.
There is no enough evidence to claim that there is a difference between the two population proportions.