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Marta_Voda [28]
3 years ago
11

4. Dean Pelton wants to perform calculations to impress the accreditation consultants, but upon asking for information about GPA

s at Greendale Community College, Chang only tells Pelton that the GPAs are distributed with a probability density function f(x) = D(2 + e −x ), 2 ≤ x ≤ 4 where D was some unknown "Duncan" constant. How many student records have to be retrieved so that the probability that the average GPA is less than 2.3 is less than 4 percent?
Mathematics
1 answer:
Leya [2.2K]3 years ago
5 0

Answer:

the minimum records to be retrieved by using Chebysher - one sided inequality is 17.

Step-by-step explanation:

Let assume that n should represent the number of the students

SO, \bar x can now be the sample mean of number of students  in GPA's

To obtain n such that P( \bar x \leq 2.3 ) \leq .04

⇒ P( \bar x \geq 2.3 ) \geq .96

However ;

E(x) = \int\limits^4_2 Dx (2+e^{-x} ) 4x = D  \\ \\ = D(e^{-x} (e^xx^2 - x-1 ) ) ^D_2 = 12.314 D

E(x^2) = D\int\limits^4_2 (2+e^{-x})dx \\ \\ = \dfrac{D}{3}[e^{-4} (2e^x x^3 -3x^2 -6x -6)]^4__2}}= 38.21 \ D

Similarly;

D\int\limits^4_2(2+ e^{-x}) dx = 1

⇒ D*(2x-e^{-x} ) |^4_2 = 1

⇒ D*4.117 = 1

⇒ D= \dfrac{1}{4.117}

\mu = E(x) = 2.991013 ; \\ \\ E(x^2) = 9.28103

∴  Var (x)  = E(x^2) - E^2(x) \\ \\  = .3348711

Now; P(\bar \geq 2.3) = P( \bar x - 2.991013 \geq 2.3 - 2.991013) \\ \\ = P( \omega  \geq .691013)  \ \ \ \  \ \ \ \ \ \ (x = E(\bar x ) - \mu)

Using Chebysher one sided inequality ; we have:

P(\omega \geq -.691013) \geq \dfrac{(.691013)^2}{Var ( \omega) +(.691013)^2}

So; (\omega = \bar x - \mu)

⇒ E(\omega ) = 0 \\ \\ Var (\omega ) = \dfrac{Var (x_i)}{n}

∴ P(\omega \geq .691013) \geq \dfrac{(.691013)^2}{\frac{.3348711}{n}+(691013)^2}

To determine n; such that ;

\dfrac{(.691013)^2}{\frac{.3348711}{n}+(691013)^2} \geq 0.96 \\ \\ \\ (.691013)^2(1-.96) \geq \dfrac{-3348711*.96}{n}

⇒ n \geq \dfrac{.3348711*.96}{.04*(.691013)^2}

n \geq 16.83125

Thus; we can conclude that; the minimum records to be retrieved by using Chebysher - one sided inequality is 17.

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Of 580580 samples of seafood purchased from various kinds of food stores in different regions of a country and genetically compa
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Answer:

a) The 99% confidence interval would be given (0.204;0.296).

b) We have 99% of confidence that the true population proportion of all seafood sold in the country that is mislabeled or misidentified is between (0.204;0.296).  

c) No that's not true. Because the necessary assumptions and conditions for the confidence interval for the proportion are satisifed, so then we can use inferential statistics to interpret the interval to the population of interest.

Step-by-step explanation:

Part a

Data given and notation  

n=580 represent the random sample taken    

X represent the seafood sold in the country that is mislabeled or misidentified by the people

\hat p=0.25 estimated proportion of seafood sold in the country that is mislabeled or misidentified by the people

\alpha=0.01 represent the significance level (no given, but is assumed)    

p= population proportion of seafood sold in the country that is mislabeled or misidentified by the people

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

The margin of error is the range of values below and above the sample statistic in a confidence interval.

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The population proportion have the following distribution

p \sim N(p,\sqrt{\frac{\hat p(1-\hat p)}{n}})

The confidence interval would be given by this formula

\hat p \pm z_{\alpha/2} \sqrt{\frac{\hat p(1-\hat p)}{n}}

For the 99% confidence interval the value of \alpha=1-0.99=0.01 and \alpha/2=0.005, with that value we can find the quantile required for the interval in the normal standard distribution.

z_{\alpha/2}=2.58

And replacing into the confidence interval formula we got:

0.25 - 2.58 \sqrt{\frac{0.25(1-0.25)}{580}}=0.204

0.25 + 2.58 \sqrt{\frac{0.25(1-0.25)}{580}}=0.296

And the 99% confidence interval would be given (0.204;0.296).

Part b

We have 99% of confidence that the true population proportion of all seafood sold in the country that is mislabeled or misidentified is between (0.204;0.296).  

Part c

A government spokesperson claimed that the sample size was too​ small, relative to the billions of pieces of seafood sold each​ year, to generalize. Is this criticism​ valid?

No that's not true. Because the necessary assumptions and conditions for the confidence interval for the proportion are satisifed, so then we can use inferential statistics to interpret the interval to the population of interest.

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