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erik [133]
4 years ago
11

Please help problem 3 and 4show workfind the value of x, y and z​

Mathematics
1 answer:
ratelena [41]4 years ago
3 0

Answer:

Step-by-step explanation:

The altitude to the hypotenuse of a right triangle create two smaller triangles, all of which are similar to the original. This means corresponding sides are proportional.

3. Using the above relationship, ...

short-side/hypotenuse = 8/y = y/(8+23)

y^2 = 8·31

y = 2√62

__

long-side/hypotenuse = z/(8+23) = 23/z

z^2 = 23·31

z = √713

__

short-side/long-side = 8/x = x/23

x^2 = 8·23

x = 2√46

_____

4. The picture is fuzzy, but we think the lengths are 25 and 5. If they're something else, use the appropriate numbers. Using the same relations we used for problem 3,

y = √(5·25) = 5√5 . . . . . . . = √(short segment × hypotenuse)

z = √(20·25) = 10√5 . . . . . = √(long segment × hypotenuse)

x = √(5·20) = 10 . . . . . . . . . = √(short segment × long segment)

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Each day a manufacturing plant receives a large shipment of drums of Chemical ZX-900. These drums are supposed to have a mean fi
nikdorinn [45]

Answer:

0.9544 = 95.44% probability that the average fill for the 100 drums is between 49.88 and 50.12 gallons.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score 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 p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Suppose the mean fill for the shipment is actually 50 gallons. Standard deviation of 0.6 gallons.

This means that \mu = 50, \sigma = 0.6

Sample of 100:

This means that n = 100, s = \frac{0.6}{\sqrt{100}} = 0.06

What is the probability that the average fill for the 100 drums is between 49.88 and 50.12 gallons?

This is the pvalue of Z when X = 50.12 subtracted by the pvalue of Z when X = 49.88. So

X = 50.12

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

By the Central Limit Theorem

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

Z = \frac{50.12 - 50}{0.06}

Z = 2

Z = 2 has a pvalue of 0.9772

X = 49.88

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

Z = \frac{49.88 - 50}{0.06}

Z = -2

Z = -2 has a pvalue of 0.0228

0.9772 - 0.0228 = 0.9544

0.9544 = 95.44% probability that the average fill for the 100 drums is between 49.88 and 50.12 gallons.

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