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Anastaziya [24]
3 years ago
15

How much would $500 invested at 6% interest compounded monthly be worth after 5 years? round your answer to the nearest cent.

Mathematics
2 answers:
Lady bird [3.3K]3 years ago
8 0
Use this formula: A = P(1 + r/n)^nt, where A is the amount after interest (what you are solving for), P is the amount you invested originally, r is the rate at which it was invested in decimal form, n is the number of times the compounding occurs each year, t is the time in years it is invested. It would look like this: A = 500(1 + [.06/12])^12*5.  Do inside the parenthesis first to get 1 + .005 = 1.005.  Now raise that to the 60th power (12 times 5 is 60) to get 1.34558. Now multiply that by the 500 out front to get a total amount of $674.43
GenaCL600 [577]3 years ago
5 0

Answer- $674.43


Step-by-step explanation:


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Vilka [71]

Answer:

0.0228 = 2.28% probability that the average score of the 64 golfers exceeded 76.

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 normally distributed samples are 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.

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.

In this problem, we have that:

\mu = 75, \sigma = 4, n = 64, s = \frac{4}{\sqrt{64}} = 0.5

Find the probability that the average score of the 64 golfers exceeded 76.

This is 1 subtracted by the pvalue of Z when X = 64.

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

By the Central Limit Theorem

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

Z = \frac{76 - 75}{0.5}

Z = 2

Z = 2 has a pvalue of 0.9772

1 - 0.9772 = 0.0228

0.0228 = 2.28% probability that the average score of the 64 golfers exceeded 76.

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