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mr Goodwill [35]
3 years ago
13

Hello i need help please for my testt!

Mathematics
1 answer:
blsea [12.9K]3 years ago
8 0

Answer:

it wont load

Step-by-step explanation:

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Vertex= D
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What is 12+ 12-4 %2<br> Hhhhhhhhhhhhhhhhhhhhhhhhhhh
prohojiy [21]
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If f(1) = 160 and f(n + 1) = –2f(n), what is f(4)?
lions [1.4K]

Answer:

-1280

Step-by-step explanation:

There are 2 ways you could do this. You could just do the question until you come to the end of f(4). That is likely the simplest way to do it.

f(1) = 160

f(2) = - 2 * f(1)

f(2) = -2*160

f(2) = -320

f(3) = -2 * f(2)

f(3) = -2 * - 320

f(3) = 640

f(4) = - 2 * f(3)

f(4) = - 2 * 640

f(4) = - 1280

I don't know that you could do this explicitly with any real confidence.

5 0
3 years ago
Read 2 more answers
The amount people pay for cable service varies quite a bit but the mean monthly fee is $142 and the standard deviation is $29. t
zhuklara [117]

Answer:

a) By the Central Limit Theorem, the mean is $142 and the standard deviation is $0.7488.

b) By the Central Limit Theorem, approximately normal.

c) 0.0901 = 9.01% probability that the average cable service paid by the sample of cable service customers will exceed $143

Step-by-step explanation:

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

Normal probability distribution

When the distribution is normal, we use 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.

The mean monthly fee is $142 and the standard deviation is $29.

This means that \mu = 142, \sigma = 29

Part a: what are the mean an standard deviation of the sample distribution of x hat show your work and justify your reasoning.

Sample of 1500(larger than 30).

By the Central Limit Theorem

The mean is $142

The standard deviation is s = \frac{29}{\sqrt{1500}} = 0.7488

Part b: what is the shape of the sampling distribution of x hat justify your answer.

By the Central Limit Theorem, approximately normal.

Part C: what is the probability that the average cable service paid by the sample of cable service customers will exceed $143?

This is 1 subtracted by the pvalue of Z when X = 143. So

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

By the Central Limit Theorem

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

Z = \frac{143 - 142}{0.7488}

Z = 1.34

Z = 1.34 has a pvalue of 0.9099

1 - 0.9099 = 0.0901

0.0901 = 9.01% probability that the average cable service paid by the sample of cable service customers will exceed $143

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8 i think so it might 
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