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natka813 [3]
2 years ago
7

PLEASE HELPP!! DID I DO IT RIGHT???

Mathematics
1 answer:
astra-53 [7]2 years ago
8 0

Answer:

yea haha good job :-)

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A triangle has side lengths of (6a - 36) centimeters, (5a + 5c) centimeters, and (8c - b) centimeters. Which expression represen
likoan [24]

Answer:

11a + 13c -b - 36

Step-by-step explanation:

We add all the sides together because we're looking for perimeter.

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2 years ago
Identify the question that is NOT statistical.
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<span>A)What is the maximum number of swimmers allowed on a swim team?</span>
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What do you say when you see an empty parrot cage?
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Oh no my parrot is missing
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3 years ago
Suppose a batch of metal shafts produced in a manufacturing company have a population standard deviation of 1.3 and a mean diame
lbvjy [14]

Answer:

54.86% probability that the mean diameter of the sample shafts would differ from the population mean by more than 0.1 inches

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 normally distributed samples are 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 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.

In this problem, we have that:

\mu = 208, \sigma = 1.3, n = 60, s = \frac{1.3}{\sqrt{60}} = 0.1678

What is the probability that the mean diameter of the sample shafts would differ from the population mean by more than 0.1 inches

Lesser than 208 - 0.1 = 207.9 or greater than 208 + 0.1 = 208.1. Since the normal distribution is symmetric, these probabilities are equal, so we find one of them and multiply by 2.

Lesser than 207.9.

pvalue of Z when X = 207.9. So

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

By the Central Limit Theorem

Z = \frac{207.9 - 208}{0.1678}

Z = -0.6

Z = -0.6 has a pvalue of 0.2743

2*0.2743 = 0.5486

54.86% probability that the mean diameter of the sample shafts would differ from the population mean by more than 0.1 inches

6 0
3 years ago
I need help fr!! ignore the writing lol
Romashka [77]

Answer:

-40

Step-by-step explanation:

(-7)(5)-5=-35-5=-40

8 0
2 years ago
Read 2 more answers
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