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andrew11 [14]
4 years ago
6

(-3/7) divided by (-1 1/14)hurry!

Mathematics
1 answer:
7nadin3 [17]4 years ago
8 0

Answer:

\frac{45}{98}

Step-by-step explanation:

We have -\frac{3}{7} /(-1 \frac{1}{14} )

The first thing that we can do is to remove the mixed number

-\frac{3}{7} /(-\frac{15}{14} )

When you divide by a fraction, you can instead multiply by the reciprocal, which is that same fraction flipped upside down.

-\frac{3}{7} *(-\frac{15}{14} )

Now, we can multiply across the top and the bottom

\frac{45}{98}

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The probability is 0.5 tiles will be green

Step-by-step explanation:

Hope this helps

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Which comparison statement is true? A. 7.24 < 7.240 B. 7.24 > 7.240 C. 7.24 = 7.240
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$22.00+$14.00= <br> answer this
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Step-by-step explanation:

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3 years ago
Solve the simultaneous equations y=3x+2 and y=x+6
kogti [31]

Answer:

x=2

Step-by-step explanation:

y=3x+2

y=x+6

Since you're stating that, they both equal because equation is equated to equation 2 because of the Y.

Therefore, substitute into both equations as shown:

3x+2=x+6

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5 0
3 years ago
Andrew plans to retire in 32 years. He plans to invest part of his retirement funds in stocks, so he seeks out information on pa
Debora [2.8K]

Answer:

a) 0.0885 = 8.85% probability that the mean annual return on common stocks over the next 40 years will exceed 13%.

b) 0.4129 = 41.29% probability that the mean return will be less than 8%

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 8.7% and standard deviation 20.2%.

This means that \mu = 8.7, \sigma = 20.2

40 years:

This means that n = 40, s = \frac{20.2}{\sqrt{40}}

(a) What is the probability (assuming that the past pattern of variation continues) that the mean annual return on common stocks over the next 40 years will exceed 13%?

This is 1 subtracted by the pvalue of Z when X = 13. So

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

By the Central Limit Theorem

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

Z = \frac{13 - 8.7}{\frac{20.2}{\sqrt{40}}}

Z = 1.35

Z = 1.35 has a pvalue of 0.9115

1 - 0.9115 = 0.0885

0.0885 = 8.85% probability that the mean annual return on common stocks over the next 40 years will exceed 13%.

(b) What is the probability that the mean return will be less than 8%?

This is the pvalue of Z when X = 8. So

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

Z = \frac{8 - 8.7}{\frac{20.2}{\sqrt{40}}}

Z = -0.22

Z = -0.22 has a pvalue of 0.4129

0.4129 = 41.29% probability that the mean return will be less than 8%

8 0
3 years ago
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