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yawa3891 [41]
3 years ago
10

Victor has a credit card with an APR of 13.66%, compounded monthly. He currently owes a balance of $1,349.34. Assuming that Vict

or makes no purchases or payments, how much will he owe after one year, to the nearest cent?
Mathematics
2 answers:
konstantin123 [22]3 years ago
4 0
<span>A = P (1 + r/n)^<span>nt
A = </span></span><span>1,349.34(1+0.1366/12)^12
A = 1545.65

answer: </span>he will owe $1545.65 after one year
valentinak56 [21]3 years ago
3 0

Answer:

$1545.65.

Step-by-step explanation:

We have been given that Victor has a credit card with an APR of 13.66%, compounded monthly. He currently owes a balance of $1,349.34.

To solve our given problem we will use compound interest formula.

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

A = Final amount after t years,

P = Principal amount,

r = Interest rate in decimal form,

n = Number of times interest is compounded per year,

t = Time in years.

Let us convert our given interest rate in decimal form.

13.66\%=\frac{13.66}{100}=0.1366

Upon substituting our given values in compound interest formula we will get,

A=\$1,349.34(1+\frac{0.1366}{12})^{12*1}

A=\$1,349.34(1+0.011383333)^{12}

A=\$1,349.34(1.011383333)^{12}

A=\$1,349.34*1.145485275522

A=\$1,545.64910167397\approx \$1545.65

Therefore, Victor will owe an amount of $1545.65 after one year.

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What is 4z(6x+7y)?<br><br> Please help!
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Annual starting salaries in a certain region of the U. S. for college graduates with an engineering major are normally distribut
defon

Answer:

0.8665 = 86.65% probability that the sample mean would be at least $39000

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

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

In a set with mean \mu and standard deviation \sigma, the z-score 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 p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Mean $39725 and standard deviation $7320.

This means that \mu = 39725, \sigma = 7320

Sample of 125:

This means that n = 125, s = \frac{7320}{\sqrt{125}} = 654.72

The probability that the sample mean would be at least $39000 is about?

This is 1 subtracted by the pvalue of Z when X = 39000. So

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

By the Central Limit Theorem

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

Z = \frac{39000 - 39725}{654.72}

Z = -1.11

Z = -1.11 has a pvalue of 0.1335

1 - 0.1335 = 0.8665

0.8665 = 86.65% probability that the sample mean would be at least $39000

4 0
2 years ago
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