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Klio2033 [76]
3 years ago
10

The price of a particular stock is represented by the linear equation y=-0.91x+103.47

Mathematics
2 answers:
Mila [183]3 years ago
8 0

Answer:

so A if any one asks

Step-by-step explanation:

Mama L [17]3 years ago
4 0

To find the price of the stock after 12 weeks, you would have to plug in 12 to x

That would make your equation: y = -0.91(12) + 103.47

Then, you solve:

-0.91(12) would be -10.12

Your equation will now look like this:

y = - 10.12 + 103.47

Then you add -10.12 to 103.47

-10.12 + 103.47 = 92.55

y = 92.55

After 12 weeks, the price of the stocks would be $92.55

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Answer:

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Step-by-step explanation:

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3 years ago
The mean life of a television set is 119119 months with a standard deviation of 1414 months. If a sample of 7474 televisions is
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Answer:

0.5034 = 50.34% probability that the sample mean would differ from the true mean by less than 1.1 months

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 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:

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In this problem, we have that:

\mu = 119, \sigma = 14, n = 74, s = \frac{14}{\sqrt{74}} = 1.6275

What is the probability that the sample mean would differ from the true mean by less than 1.11 months?

This is the pvalue of Z when X = 119 + 1.1 = 120.1 subtracted by the pvalue of Z when X = 119 - 1.1 = 117.9. So

X = 120.1

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

By the Central Limit Theorem

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

Z = \frac{120.1 - 119}{1.6275}

Z = 0.68

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X = 117.9

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

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Z = -0.68 has a pvalue of 0.2483

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0.5034 = 50.34% probability that the sample mean would differ from the true mean by less than 1.1 months

3 0
3 years ago
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Answer:

He's correct.

Step-by-step explanation:

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