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Evgesh-ka [11]
2 years ago
11

Graph the solution to the following system of inequalities.

Mathematics
1 answer:
Nostrana [21]2 years ago
8 0

Answer:

Download phot math

Step-by-step explanation:

:)

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John drives to work five days a week the month of August round trip between home and his job is 7.56 miles part a: estimate the
anzhelika [568]

Answer: 113.4 miles

Step-by-step explanation:

I think this correct because 7.56 x 5 = 37.8   then 21 days is 3 weeks so 37.8 x 3 = 113.4

8 0
2 years ago
Simplify (X2/3) ^4/5
Flura [38]

The answer to your questions is x8/15. Hope this helps!

7 0
3 years ago
A spinner is divided into 9 equal parts. What is the probability of it landing on an even number?
Anestetic [448]

Answer:

4/9

Step-by-step explanation:

8 0
2 years ago
Two sides of an isosceles triangle measures 10 and 10. What is true about the third side?
zvonat [6]
The 3rd side is not the same length of the first 2 sides.
6 0
3 years ago
Parts being manufactured at a plant are supposed to weigh 65 grams. Suppose the distribution of weights has a Normal distributio
andrew-mc [135]

Answer:

0.64%.

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.

Mean of 75 grams and a standard deviation of 22 grams.

This means that \mu = 75, \sigma = 22

Sample of 144:

This means that n = 144, s = \frac{22}{\sqrt{144}} = 1.8333

More than 80 or less than 70:

Both are the same distance from the mean, so we find one probability and multiply by 2.

The probability that it is less than 70 is the pvalue of Z when X = 70. So

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

By the Central Limit Theorem

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

Z = \frac{70 - 75}{1.8333}

Z = -2.73

Z = -2.73 has a pvalue of 0.0032

2*0.0032 = 0.0064.

0.0064*100% = 0.64%

The probability is 0.64%.

3 0
3 years ago
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