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Jobisdone [24]
3 years ago
5

Someone please help me with this I really don’t know it ASAP

Mathematics
2 answers:
maxonik [38]3 years ago
8 0

Answer:

light blue D-E

Step-by-step explanation:

it is a 180 and leads to F if you continue with the line

yur welcome

Valentin [98]3 years ago
3 0

Answer:

DE

Step-by-step explanation:

because its the only line that has F on it

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The proper natation for a normal distribution with a mean of 250 and a standard deviation of 25 is?
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a recipe uses 2 cups of milk per (1) serving. How many servings can be made by using 1 gallon of milk?
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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

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 = 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.

6 0
2 years ago
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