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pishuonlain [190]
3 years ago
11

Since 2003 median home prices in Midvale, UT have been growing exponentially at roughly 4.7 % per year. If you had purchased a h

ouse in Midvale, UT for $ 172000 in 2004 in what year would the home be worth $ 249000 ?
Mathematics
1 answer:
Kipish [7]3 years ago
8 0

Answer:

The home would be worth $249000 during the year of 2012.

Step-by-step explanation:

The price of the home in t years after 2004 can be modeled by the following equation:

P(t) = P(0)(1+r)^{t}

In which P(0) is the price of the house in 2004 and r is the growth rate.

Since 2003 median home prices in Midvale, UT have been growing exponentially at roughly 4.7 % per year.

This means that r = 0.047

$172000 in 2004

This means that P(0) = 172000

What year would the home be worth $ 249000 ?

t years after 2004.

t is found when P(t) = 249000. So

P(t) = P(0)(1+r)^{t}

249000 = 172000(1.047)^{t}

(1.047)^{t} = \frac{249000}{172000}

\log{(1.047)^{t}} = \log{\frac{249000}{172000}}

t\log(1.047) = \log{\frac{249000}{172000}}

t = \frac{\log{\frac{249000}{172000}}}{\log(1.047)}

t = 8.05

2004 + 8.05 = 2012

The home would be worth $249000 during the year of 2012.

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Answer:

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Step-by-step explanation:

<u><em>The question is </em></u>

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Part b) How old is Kevin?

Let

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Equate equation A and equation B

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x=4(2)=8\ years

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A professor pays 25 cents for each blackboard error made in lecture to the student who pointsout the error. In a career ofnyears
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Answer:

(a) The probability that <em>Y</em>₂₀ exceeds 1000  is 3.91 × 10⁻⁶.

(b) <em>n</em> = 28.09

Step-by-step explanation:

The random variable <em>Y</em>ₙ is defined as the total numbers of dollars paid in <em>n</em> years.

It is provided that <em>Y</em>ₙ can be approximated by a Gaussian distribution, also known as Normal distribution.

The mean and standard deviation of <em>Y</em>ₙ are:

\mu_{Y_{n}}=40n\\\sigma_{Y_{n}}=\sqrt{100n}

(a)

For <em>n</em> = 20 the mean and standard deviation of <em>Y</em>₂₀ are:

\mu_{Y_{n}}=40n=40\times20=800\\\sigma_{Y_{n}}=\sqrt{100n}=\sqrt{100\times20}=44.72\\

Compute the probability that <em>Y</em>₂₀ exceeds 1000 as follows:

P(Y_{n}>1000)=P(\frac{Y_{n}-\mu_{Y_{n}}}{\sigma_{Y_{n}}}>\frac{1000-800}{44.72})\\=P(Z>  4.47)\\=1-P(Z

**Use a <em>z </em>table for probability.

Thus, the probability that <em>Y</em>₂₀ exceeds 1000  is 3.91 × 10⁻⁶.

(b)

It is provided that P (<em>Y</em>ₙ > 1000) > 0.99.

P(Y_{n}>1000)=0.99\\1-P(Y_{n}

The value of <em>z</em> for which P (Z < z) = 0.01 is 2.33.

Compute the value of <em>n</em> as follows:

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The last equation is a quadratic equation.

The roots of a quadratic equation are:

n=\frac{-b\pm\sqrt{b^{2}-4ac}}{2a}

a = 16

b = -805.4289

c = 10000

On solving the last equation the value of <em>n</em> = 28.09.

8 0
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