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Mandarinka [93]
3 years ago
5

An executive invests $22,000 some at 7% ad some at 6% annual interest. If he receives an annual return of $1,420, how much is in

vested at each rate?
Mathematics
1 answer:
34kurt3 years ago
8 0

Answer:

he invested $10,000 at 7% and $12,000 at 6%

Step-by-step explanation:

  • There are 2 equations that appear from this problem
  • X+Y=22,000 and 0.07x + 0.06y = 1420
  • Lets start by simplifying X+Y=22000

Y = 22000 - x

  • now plug this into the Y value for the other equation

0.07x + 0.06(22000-x) = 1420

0.07x + 1320 -0.06x = 1420

0.01x = 100

X = 10000

  • now plug 10000 into x for the simplified equation

Y = 22000 - 10000

Y = 12000

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Using the Central Limit Theorem, we have that:

a) Yes, it can be used, as np > 10 and n(1 - p) > 10.

b) There is a 0.0475 = 4.75% probability that the proportion in the random sample of 100 orders is the same as the proportion found in the audit sample or less.

<h3>Normal Probability Distribution</h3>

The z-score of a measure X of a normally distributed variable with mean \mu and standard deviation \sigma is given by:

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

  • The z-score measures how many standard deviations the measure is above or below the mean.
  • Looking at the z-score table, the p-value associated with this z-score is found, which is the percentile of X.
  • By the Central Limit Theorem, for a proportion p in a sample of size n, the sampling distribution of sample proportion is approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1 - p)}{n}}, as long as np \geq 10 and n(1 - p) \geq 10.

For the sample, we have that:

  • np = 85 > 10.
  • n(1 - p) = 15 > 10.

Hence the normal approximation can be used.

As for part B, if we have p = 0.9 and n = 100, the mean and the standard error are given by:

  • \mu = p = 0.9.
  • s = \sqrt{\frac{p(1 - p)}{n}} = \sqrt{\frac{0.9(0.1)}{100}} = 0.03

The probability of a sample proportion of 85% of less is the <u>p-value of Z when X = 0.85</u>, hence:

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

By the Central Limit Theorem

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

Z = \frac{0.85 - 0.9}{0.03}

Z = -1.67

Z = -1.67 has a p-value of 0.0475.

There is a 0.0475 = 4.75% probability that the proportion in the random sample of 100 orders is the same as the proportion found in the audit sample or less.

More can be learned about the Central Limit Theorem at brainly.com/question/24663213

#SPJ1

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