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S_A_V [24]
4 years ago
12

How many different ways can you write 10 to the sixth power?

Mathematics
1 answer:
Aleksandr [31]4 years ago
4 0
10⁶ = 10.10.10.10.10.10

10<span>⁶ = 1,000,000</span>

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Mark jumped 6 feet 9 inches in the long jump competition and George jumped 8 feet 4 inches. How many inches farther did George j
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1 foot and 5 inches.

Step-by-step explanation:

He jumped 6 ft. 9 inch. 6.9+1.5 = 8.4

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Write 5√20 in exponental form​
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I have 5 quarters and 7 pennies. What fraction of the coins are pennies?
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Of the total population of the United States, 20% live in the northeast. If 200 residents of the United States are selected at r
Snezhnost [94]

Answer:

0.0465 = 4.65% probability that at least 50 live in the northeast.

Step-by-step explanation:

I am going to use the normal approximation to the binomial to solve this question.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

E(X) = np

The standard deviation of the binomial distribution is:

\sqrt{V(X)} = \sqrt{np(1-p)}

Normal probability distribution

Problems of normally distributed samples can be 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.

When we are approximating a binomial distribution to a normal one, we have that \mu = E(X), \sigma = \sqrt{V(X)}.

In this problem, we have that:

n = 200, p = 0.2

So

\mu = E(X) = np = 200*0.2 = 40

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{200*0.2*0.8} = 5.65685

Approximate the probability that at least 50 live in the northeast.

Using continuity correction, this is P(X \geq 50 - 0.5) = P(X \geq 49.5, which is 1 subtracted by the pvalue of Z when X = 49.5. So

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

Z = \frac{49.5 - 40}{5.65685}

Z = 1.68

Z = 1.68 has a pvalue of 0.9535

1 - 0.9535 = 0.0465

0.0465 = 4.65% probability that at least 50 live in the northeast.

3 0
4 years ago
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