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Anton [14]
4 years ago
6

Upon graduation from​ college, Warren Roberge was able to defer payment on his ​$22,000 student loan for 3 months. Since the int

erest will no longer be paid on his​ behalf, it will be added to the principal until payments begin. If the interest is 6.94 ​% compounded monthly ​, what will the principal amount be when he must begin repaying his​ loan?
Mathematics
2 answers:
AURORKA [14]4 years ago
6 0

Answer:

The principal amount be when he must begin repaying his​ loan is $22383.911.

Step-by-step explanation:

Given : Upon graduation from​ college, Warren Roberge was able to defer payment on his ​$22,000 student loan for 3 months. If the interest is 6.94 ​% compounded monthly.

To find : What will the principal amount be when he must begin repaying his​ loan?

Solution :

Using compound interest formula,

A=P(1+\frac{r}{n})^{nt}

Where,

A is the amount

P is the principal P=$22,000

r is the rate r=6.94%=0.0694

t is the time t=3 months

Into years, t=\frac{3}{12}=\frac{1}{4}

n is the number of period n=12

Substitute the value in the formula,

A=22000(1+\frac{0.0694}{12})^{12\times \frac{1}{4}}

A=22000(1+0.005783)^{3}

A=22000(1.005783)^{3}

A=22000(1.01745)

A=22383.911

The principal amount be when he must begin repaying his​ loan is $22383.911.

makvit [3.9K]4 years ago
4 0
It sounds to me as I read it, as the principal P, will have the 3 months of interest added, because Warren deferred payments for 3 months, but that doesn't let him off the hook on the interest payments, so what the loaning bank did is say, "ok, start paying it in 3 months, but we'll accumulate the monthly interest to it".

so in short what is a principal of 22,000 accumulating 6.94% monthly compounding interest rate for 3 months?

bearing in mind that 3 months is not even a year, since there are 12 months in a year, 3 months is really just 3/12 year.

\bf \qquad \textit{Compound Interest Earned Amount}
\\\\
A=P\left(1+\frac{r}{n}\right)^{nt}
\quad 
\begin{cases}
A=\textit{accumulated amount}\\
P=\textit{original amount deposited}\to &\$22000\\
r=rate\to 6.94\%\to \frac{6.94}{100}\to &0.0694\\
n=
\begin{array}{llll}
\textit{times it compounds per year}\\
\textit{montly, thus twelve}
\end{array}\to &12\\
t=years\to \frac{3}{12}\to &\frac{1}{4}
\end{cases}
\\\\\\


\bf A=22000\left(1+\frac{0.0694}{12}\right)^{12\cdot \frac{1}{4}}\implies A=2000\left( 1+\frac{347}{60000} \right)^3
\\\\\\
A=22000\left( \frac{60347}{60000} \right)^3
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That's why SAS rule is correct.

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1.69\times 10^3feet/million year

Step-by-step explanation:

We are given that

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Rate of basalt filling in the valley=\frac{Elevation\;of\;top\;of\;basalt\;in\;valley-elevation\;of\;bottom\;of\;basalt\;in\;valley}{age\;of\;bottom\;of\;basalt\;in\;valley-age\;of\;top\;of\;basalt\;in\;valley}

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In the following problem, check that it is appropriate to use the normal approximation to the binomial. Then use the normal dist
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Answer:

a) 0.9920 = 99.20% probability that 15 or more will live beyond their 90th birthday

b) 0.2946  = 29.46% probability that 30 or more will live beyond their 90th birthday

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d) 0.0034 = 0.34% probability that more than 40 will live beyond their 90th birthday

Step-by-step explanation:

We solve this question using the normal approximation to the binomial distribution.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

E(X) = np

The standard deviation of the binomial distribution is:

\sqrt{V(X)} = \sqrt{np(1-p)}

Normal probability distribution

Problems of normally distributed distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

When we are approximating a binomial distribution to a normal one, we have that \mu = E(X), \sigma = \sqrt{V(X)}.

In this problem, we have that:

Sample of 723, 3.7% will live past their 90th birthday.

This means that n = 723, p = 0.037.

So for the approximation, we will have:

\mu = E(X) = np = 723*0.037 = 26.751

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{723*0.037*0.963} = 5.08

(a) 15 or more will live beyond their 90th birthday

This is, using continuity correction, P(X \geq 15 - 0.5) = P(X \geq 14.5), which is 1 subtracted by the pvalue of Z when X = 14.5. So

Z = \frac{X - \mu}{\sigma}

Z = \frac{14.5 - 26.751}{5.08}

Z = -2.41

Z = -2.41 has a pvalue of 0.0080

1 - 0.0080 = 0.9920

0.9920 = 99.20% probability that 15 or more will live beyond their 90th birthday

(b) 30 or more will live beyond their 90th birthday

This is, using continuity correction, P(X \geq 30 - 0.5) = P(X \geq 29.5), which is 1 subtracted by the pvalue of Z when X = 29.5. So

Z = \frac{X - \mu}{\sigma}

Z = \frac{29.5 - 26.751}{5.08}

Z = 0.54

Z = 0.54 has a pvalue of 0.7054

1 - 0.7054 = 0.2946

0.2946  = 29.46% probability that 30 or more will live beyond their 90th birthday

(c) between 25 and 35 will live beyond their 90th birthday

This is, using continuity correction, P(25 - 0.5 \leq X \leq 35 + 0.5) = P(X 24.5 \leq X \leq 35.5), which is the pvalue of Z when X = 35.5 subtracted by the pvalue of Z when X = 24.5. So

X = 35.5

Z = \frac{X - \mu}{\sigma}

Z = \frac{35.5 - 26.751}{5.08}

Z = 1.72

Z = 1.72 has a pvalue of 0.9573

X = 24.5

Z = \frac{X - \mu}{\sigma}

Z = \frac{24.5 - 26.751}{5.08}

Z = -0.44

Z = -0.44 has a pvalue of 0.3300

0.9573 - 0.3300 = 0.6273

0.6273 = 62.73% probability that between 25 and 35 will live beyond their 90th birthday.

(d) more than 40 will live beyond their 90th birthday

This is, using continuity correction, P(X > 40+0.5) = P(X > 40.5), which is 1 subtracted by the pvalue of Z when X = 40.5. So

Z = \frac{X - \mu}{\sigma}

Z = \frac{40.5 - 26.751}{5.08}

Z = 2.71

Z = 2.71 has a pvalue of 0.9966

1 - 0.9966 = 0.0034

0.0034 = 0.34% probability that more than 40 will live beyond their 90th birthday

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Step-by-step explanation:

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