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Arte-miy333 [17]
2 years ago
7

Mi-young is cooking kalguksu for a large family kalgusku is a korean soup with noodles. She makes two kinds of kalguksu,chicken

and seafood.
Mi-young makes 24 cups of seafood kalguksu. This is 60% of the total kalguksu she makes

HELP I DONT PAY ATTENTION IN CLASS
​

Mathematics
1 answer:
arlik [135]2 years ago
5 0

\mathfrak{\huge{\orange{\underline{\underline{AnSwEr:-}}}}}

Actually Welcome to the Concept of the ratio and percentages.

let's be the total kalguksu soup quantity be x

hence, 60% of x = 24 cups, so we get as

===> 60/100 * x = 24

=> 0.6*x = 24

hence, x ==> 24/0.6

=====> x = 40 cups

hence the answer is 40 cups are in total kalguksu soup.

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Ali bought 20 dozen oranges 10% of them were rotten. How many oranges were good ?​
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Step-by-step explanation:

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The operation manager at a tire manufacturing company believes that the mean mileage of a tire is 33,208 miles, with a standard
avanturin [10]

Answer:

There is a 92.32% probability that the sample mean would differ from the population mean by less than 633 miles in a sample of 49 tires if the manager is correct.

Step-by-step explanation:

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.

Central Limit Theorem

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

In this problem, we have that:

The operation manager at a tire manufacturing company believes that the mean mileage of a tire is 33,208 miles, with a standard deviation of 2503 miles.

This means that \mu = 33208, \sigma = 2503.

What is the probability that the sample mean would differ from the population mean by less than 633 miles in a sample of 49 tires if the manager is correct?

This is the pvalue of Z when X = 33208+633 = 33841 subtracted by the pvalue of Z when X = 33208 - 633 = 32575

By the Central Limit Theorem, we have t find the standard deviation of the sample, that is:

s = \frac{\sigma}{\sqrt{n}} = \frac{2503}{\sqrt{49}} = 357.57

So

X = 33841

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

Z = \frac{33841 - 33208}{357.57}

Z = 1.77

Z = 1.77 has a pvalue of 0.9616

X = 32575

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

Z = \frac{32575- 33208}{357.57}

Z = -1.77

Z = -1.77 has a pvalue of 0.0384.

This means that there is a 0.9616 - 0.0384 = 0.9232 = 92.32% probability that the sample mean would differ from the population mean by less than 633 miles in a sample of 49 tires if the manager is correct.

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Step-by-step explanation:

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