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RideAnS [48]
3 years ago
11

The frequency (F) and length (L) of a wave are related by the following formula: F x L = 3.0 x 10^10. Consider that the waveleng

th of x-rays is 1 x 10^−11. What is the frequency of x-rays?
Mathematics
1 answer:
Ede4ka [16]3 years ago
5 0
F x L = 3x10^10
L = 1x10^-11
F= 3x10^10 / 1x10^-11 = 3x10^21 unit

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Because of your favorite lemonade it is $3.84 for 3 gallons. Write this as an unit rate
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Consider the probability that greater than 94 out of 153 people will not get the flu this winter. Assume the probability that a
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Answer:

0.8212 = 82.12% probability that greater than 94 out of 153 people will not get the flu this winter.

Step-by-step explanation:

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:

p = 0.65, n = 153. So

\mu = E(X) = 153*0.65 = 99.45

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{153*0.65*0.35} = 5.9

Consider the probability that greater than 94 out of 153 people will not get the flu this winter

This probability is 1 subtracted by the pvalue of Z when X = 94. So

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

Z = \frac{94 - 99.45}{5.9}

Z = -0.92

Z = -0.92 has a pvalue of 0.1788

1 - 0.1788 = 0.8212

0.8212 = 82.12% probability that greater than 94 out of 153 people will not get the flu this winter.

7 0
3 years ago
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