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Sedaia [141]
2 years ago
15

A company's profit C (in thousands of dollars) can be modeled by the polynomial function C = - 5x ^ 3 + 6x ^ 2 + 15x , where x i

s the number of items produced in thousands. The profit is $14,000 for producing 2000 items. What other number of items would produce about the same profit?
Mathematics
1 answer:
steposvetlana [31]2 years ago
4 0

Answer:

849 items.

Step-by-step explanation:

Given that the profit C (in thousands of dollars) for x thousands of items related as

C = - 5x ^ 3 + 6x ^ 2 + 15x \\\\\Rightarrow -5x^3+6x^2+15x -C=0\cdots(i)

As the profit is $14,000 for producing 2000 items, so

C= 14 thousand dollars and

x= 2 thousand items.

Putting C= 14 in the equation ( we have),

-5x^3+6x^2+15x -14=0\cdots(ii)

Now, x=2 is one of the solutions to the equation (ii), so (x-2) is a factor of the equation (ii), we have

(x-2)(-5x^2-4x+7)=0 \\\\\Rightarrow x-2=2 \; or \; -5x^2-4x+7=0

We have the given solution for x-2=0, so sloving -5x^2-4x+7=0 for other solutions.

-5x^2-4x+7=0 \\\\\Rightarrow x= \frac {-(-4)\pm \sqrt {(-4)^2-4\times (-5)7}}{2\times (-5)} \\\\\Rightarrow x= \frac {4\pm \sqrt {156}}{2\times (-5)} \\\\\Rightarrow x= \frac {4\pm 12.49}{2\times (-5)} \\\\\Rightarrow x = \frac {4+ 12.49}{2\times (-5)}, \frac {4- 12.49}{2\times (-5)} \\\\\Rightarrow x = -1.649, 0.849

As the number of items cant be negative, so x= 0.849 thousand is the other number of items.

Hence, the other number of items for the same profit is 849 items.

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d) This value is c = 20.6153.

Step-by-step explanation:

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}}.

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.

In this problem, we have that:

A particular variety of watermelon weighs on average 20.4 pounds with a standard deviation of 1.23 pounds. This means that \mu = 20.4, \sigma = 1.23

Consider the sample mean weight of 100 watermelons of this variety. This means that n = 100.

a. What is the expected value of the sample mean weight? Give an exact answer.

By the Central Limit Theorem, it is the same as the mean of the population. So the expected value of the sample mean weight is 20.4 pounds.

b. What is the standard deviation of the sample mean weight? Give your answer to four decimal places.

By the Central Limit Theorem, that is:

s = \frac{\sigma}{\sqrt{n}} = \frac{1.23}{\sqrt{100}} = 0.123

The standard deviation of the sample mean weight is 0.123.

c. What is the approximate probability the sample mean weight will be less than 20.27?

This is the pvalue of Z when X = 20.27.

Since we are working with the sample mean, we use s instead of \sigma in the Z score formula

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

Z = \frac{20.27 - 20.4}{0.123}

Z = -1.06

Z = -1.06 has a pvalue of 0.1446.

This means that there is a 14.46% probability the sample mean weight will be less than 20.27.

d. What is the value c such that the approximate probability the sample mean will be less than c is 0.96?

This is the value of X = c that is in the 96th percentile, that is, it's Z score has a pvalue 0.96.

So we use Z = 1.75

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

1.75 = \frac{c - 20.4}{0.123}

c - 20.4 = 0.123*1.75

c = 20.6153

This value is c = 20.6153.

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Answer:

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