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zhuklara [117]
3 years ago
14

One canned juice drink is 15% orange juice another is 10% orange juice how many liters of each should be mixed together in order

to get 5 L that is 14% orange juice

Mathematics
1 answer:
vfiekz [6]3 years ago
7 0
\bf \begin{array}{lccclll}
&quantity(L)&concentration&
\begin{array}{llll}
concentrated\\
quantity
\end{array}\\
&-----&-------&-------\\
\textit{15\% juice}&x&0.15&0.15x\\
\textit{10\% juice}&y&0.10&0.10y\\
-----&-----&-----&-----\\
mixture&5&0.14&(5)(0.14)
\end{array}

whatever the amounts of "x" and "y" are, they must add up to 5Liters
thus x + y = 5

and whatever the concentrated quantity is in each, they must add up to (5)(0.14)

notice, that we use the decimal notation for the amount of juice concentration, that is, 15% is just 15/100 or 0.15, and 14% is just 14/100 or 0.14 and so on, recall that "whatever% of something" is just (whatever/100)*something

thus    \bf \begin{cases}
x+y=5\implies \boxed{y}=5-x\\\\
0.15x+0.10y=(5)(0.14)\\
----------\\
0.15x+0.10\left(\boxed{5-x}  \right)=(5)(0.14)
\end{cases}

solve for "x", to see how much of the 15% juice will be needed

what about "y"?  well, y = 5 - x

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Assume that 24.5% of people have sleepwalked. Assume that in a random sample of 1478 adults, 369 have sleepwalked. a. Assuming t
solniwko [45]

Answer:

a) 0.3483 = 34.83% probability that 369 or more of the 1478 adults have sleepwalked.

b) 369 < 403.4, which means that 369 is less than 2.5 standard deviations above the mean, and thus, a result of 369 is not significantly high.

c) Since the sample result is not significant, it suggests that the rate of 24.5% is a good estimate for the percentage of people that have sleepwalked.

Step-by-step explanation:

We 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)}

A result is considered significantly high if it is more than 2.5 standard deviations above the mean.

Normal probability distribution

Problems of normally distributed distributions 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)}.

Assume that 24.5% of people have sleepwalked.

This means that p = 0.245

Sample of 1478 adults:

This means that n = 1478

Mean and standard deviation:

\mu = 1478*0.245 = 362.11

\sigma = \sqrt{1478*0.245*0.755} = 16.5346

a. Assuming that the rate of 24.5% is correct, find the probability that 369 or more of the 1478 adults have sleepwalked.

Using continuity correction, this is P(X \geq 369 - 0.5) = P(X \geq 368.5), which is 1 subtracted by the p-value of Z when X = 368.5.

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

Z = \frac{368.5 - 362.11}{16.5346}

Z = 0.39

Z = 0.39 has a p-value of 0.6517

1 - 0.6517 = 0.3483

0.3483 = 34.83% probability that 369 or more of the 1478 adults have sleepwalked.

b. Is that result of 369 or more significantly high?

362.11 + 2.5*16.5346 = 403.4

369 < 403.4, which means that 369 is less than 2.5 standard deviations above the mean, and thus, a result of 369 is not significantly high.

c. What does the result suggest about the rate of 24.5%?

Since the sample result is not significant, it suggests that the rate of 24.5% is a good estimate for the percentage of people that have sleepwalked.

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