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amid [387]
3 years ago
14

Jenny, Noah, and Mary baked cookies for the class party. They baked 15, 18, and 17 cookies respectively. What percent of all coo

kies did Jenny bake?
Mathematics
1 answer:
Andrei [34K]3 years ago
3 0
You first add all the numbers together. 17+18+15. You get 50. Then, since Jenny baked 15 cookies, (respectively) you take 15 over 50 and times it by 100 to get 30%. I’m pretty sure.
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4 cats each ate 1/4 cup of canned food and 1/4 cup of dry food. how much food did they eat altogether
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Answer: 1 cup canned and 1 cup dry, 2cups put together

Step-by-step explanation:

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FIRST RIGHT GETS BRAINLIEST
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Answer:

the answer is zero

Step-by-step explanation:

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The difference between 8 and a number is 5.
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Answer:

the answer is 3.

Step-by-step explanation:

Difference between means to subtract.

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Student records suggest that the population of students spends an average of 6.30 hours per week playing organized sports. The p
Ymorist [56]

Answer:

a) 99.24% chance HLI will find a sample mean between 5.5 and 7.1 hours.

b) 81.64% probability that the sample mean will be between 5.9 and 6.7 hours.

Step-by-step explanation:

To solve this question, it is important to know the Normal probability distribution and the Central Limit Theorem

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.

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 \frac{\sigma}{\sqrt{n}}.

In this problem, we have that:

\mu = 6.3, \sigma = 2.1, n = 49, s = \frac{2.1}{\sqrt{49}} = 0.3

A) What is the chance HLI will find a sample mean between 5.5 and 7.1 hours?

This is the pvalue of Z when X = 7.1 subtracted by the pvalue of Z when X = 5.5.

By the Central Limit Theorem, the formula for Z is:

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

X = 7.1

Z = \frac{7.1 - 6.3}{0.3}

Z = 2.67

Z = 2.67 has a pvalue of 0.9962

X = 5.5

Z = \frac{5.5 - 6.3}{0.3}

Z = -2.67

Z = -2.67 has a pvalue of 0.0038

So there is a 0.9962 - 0.0038 = 0.9924 = 99.24% chance HLI will find a sample mean between 5.5 and 7.1 hours.

B) Calculate the probability that the sample mean will be between 5.9 and 6.7 hours.

This is the pvalue of Z when X = 6.7 subtracted by the pvalue of Z when X = 5.9

X = 6.7

Z = \frac{6.7 - 6.3}{0.3}

Z = 1.33

Z = 1.33 has a pvalue of 0.9082

X = 5.9

Z = \frac{5.9 - 6.3}{0.3}

Z = -1.33

Z = -1.33 has a pvalue of 0.0918.

So there is a 0.9082 - 0.0918 = 0.8164 = 81.64% probability that the sample mean will be between 5.9 and 6.7 hours.

5 0
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mixas84 [53]

Answer:

ç

Step-by-step explanation:

8 0
3 years ago
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