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SashulF [63]
3 years ago
7

In a population distribution, a score of x=57 corresponds to z=-0.25 and a score of x=87 corresponds to z=1.25. Find the mean an

d standard deviation for the population.
Mathematics
2 answers:
Eva8 [605]3 years ago
7 0

Answer: The mean is 62 and the standard deviation is 20 for the population.

Step-by-step explanation:

Let \mu be the mean and \sigma be the standard deviation .

Formula to calculate z-score corresponds to random variable x on normal curve.

Z=\dfrac{X-\mu}{\sigma},  

Given : In a population distribution, a score of x=57 corresponds to z=-0.25 and a score of x=87 corresponds to z=1.25.

-0.25=\dfrac{57-\mu}{\sigma}\\\\-0.25\sigma=57-\mu---------(1)

1.25=\dfrac{87-\mu}{\sigma}\\\\1.25\sigma=87-\mu----------(2)

Eliminate equation(1) from equation(2), we get

1.50\sigma=30\\\\\Rightarrow\ \sigma=\dfrac{30}{1.5}=20

Put value of \sigma=20 in (1)

1.25(20)=87-\mu\\\\87-\mu=25,\\\\\Rightarrow\mu=87-25=62.

Hence, the mean is 62 and the standard deviation is 20 for the population.

Serggg [28]3 years ago
3 0

Here is dependence between scores and x-values:

Z_i=\dfrac{X_i-\mu}{\sigma},

where \mu is the mean, \sigma is standard deviation and i changes from 1 to 2.

1. When i=1, Z_1=-0.25,\ X_1=57, then

-0.25=\dfrac{57-\mu}{\sigma}.

2. When i=2, Z_2=1.25,\ X_2=87, then

1.25=\dfrac{87-\mu}{\sigma}.

Now solve the system of equations:

\left\{\begin{array}{l}-0.25=\dfrac{57-\mu}{\sigma}\\ \\1.25=\dfrac{87-\mu}{\sigma}.\end{array}\right.

\left\{\begin{array}{l}-0.25\sigma=57-\mu\\ \\1.25\sigma=87-\mu.\end{array}\right.

Subtract first equation from the second:

1.25\sigma-(-0.25\sigma)=87-57,\\ \\1.5\sigma=30,\\ \\\sigma=20.

Then

1.25=\dfrac{87-\mu}{20},\\ \\87-\mu=25,\\ \\\mu=87-25=62.

Answer: the mean is 62, the standard deviation is 20.

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a) E(X) = 6.45

b) E(X^{2} )= 57.25

c) V(X) = 15.648

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Step-by-step explanation:

a) E(X) = \sum xP(x)

E(X) = (1*0.05) + (2*0.10) + (4*0.35) + (8*0.40) + (16*0.10)\\E(X) = 6.45

b)

E(X^{2} ) = (1^{2} *0.05) + (2^{2} *0.10) + (4^{2} *0.35) + (8^{2} *0.40) + (16^{2} *0.10)\\  E(X^{2} )= 57.25

c)

V(X) = E(X^{2} ) - (E(X))^{2} \\V(X) = 57.25 - 6.45^{2} \\V(X) = 15.648

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E(3X+2) = 3E(X) + 2\\E(3X+2) = (3*6.45) + 2 \\E(3X+2) = 21.35

e)

E(3X^{2} +2) = 3E(X^{2} ) + 2\\E(3X^{2} +2) = (3*57.25) + 2 \\E(3X^{2} +2) = 173.75

f)

V(3X+2) = 3^{2} V(X)\\V(3X+2) = 9*15.648\\V(3X+2) = 140.832

g)

E(X+1) = E(X) + 1\\E(X+1) = 6.45 + 1\\E(X+1) =7.45

h)

V(X+1) = 1^{2} V(X)\\V(X+1) = 15.648

6 0
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Answer:

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We can combine them together to make 3x.

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Divide both sides by 3 to solve for x.

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Lastly, plug it in for 2x to get the price of the more expensive hat.

2(25.04) = ?

2(25.04) = 50.08

Therefore, the price of the more expensive hat is $50.08

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