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Kaylis [27]
3 years ago
5

Can someone please help?

Mathematics
2 answers:
yanalaym [24]3 years ago
4 0

Answer:

B

Step-by-step explanation:

112.5/15=7.5

RUDIKE [14]3 years ago
3 0

\frac{112.5}{15}  = 7.5 ✅

<h3><u>Step</u>-<u>by</u>-<u>step</u> <u>explanation</u>:</h3>

Option A⤵

\frac{15}{112.5}  = 75 \\ ⇢ 0.1333   ≠75

Option B⤵

\frac{112.5}{15}  = 7.5 \\ ⇢    7.5 = 7.5

Option C⤵

\frac{112.5}{15}  = 75 \\ ⇢ 7.5   ≠75

Option D⤵

\frac{15}{112.5}  = 7.5 \\ ⇢ 0.1333   ≠7.5

Hence, option B is correct.

\circ \: \: { \underline{ \boxed{ \sf{ \color{green}{Happy\:learning.}}}}}∘

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Find the missing lengths.
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Answer:

x = 5√2

Step-by-step explanation:

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3 years ago
I wasn't in school today can someone explain how to do this
Pachacha [2.7K]
You have to multiply 7 3/4 to 9.

First, turn 7 3/4 to an improper fraction which is 31/4.
Next, you multiply 31/4 to 9/1(same thing as 9) across from each other.
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4 years ago
Consider the probability that no less than 96 out of 145 people will not get the flu this winter. Assume the probability that a
dsp73

Answer:

0.1324 = 13.24% probability that no less than 96 out of 145 people will not get the flu this winter.

Step-by-step explanation:

Binomial probability distribution

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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:

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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 = 145, p = 0.61

So

\mu = E(X) = np = 145*0.61 = 88.45

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{145*0.61*0.39} = 5.87

Consider the probability that no less than 96 out of 145 people will not get the flu this winter.

More than 95 people, which is the same as 1 subtracted by the pvalue of Z when X = 95. So

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

Z = \frac{95 - 88.45}{5.87}

Z = 1.115

Z = 1.115 has a pvalue of 0.8676

1 - 0.8676 = 0.1324

0.1324 = 13.24% probability that no less than 96 out of 145 people will not get the flu this winter.

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