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nataly862011 [7]
3 years ago
5

Define z_alpha to be a z-score with an area of alpha to the right. For Example: z_0.10 means P(Z > z_0.10) = 0.10. We would a

lso have, for example; P(Z < -z_0.10) = 0.10 because of the symmetric property of the normal distribution. Questions: (a)Find P(-z_0.025 < Z < z_0.025) (b)Find P(-z_alpha/2 < Z < 2_alpha/2). (c)Find the value of z_alpha (rounded to 3 decimals) such that P(Z > z_alpha) = 0.05.
Mathematics
1 answer:
Reptile [31]3 years ago
6 0

Answer:

a) P(-z_0.025 < Z < z_0.025)

For this case we want a quantile that accumulates 0.025 of the area on the tails of the normal standard distribution, and for this case we can calculate the z value with the following excel codes:

"=NORM.INV(0.025,0,1)"

"=NORM.INV(0.025,0,1)"

And for this case the two values are :z_{crit}= \pm 1.96

b) P(-z_{\alpha/2} < Z < z_{\alpha/2})

For this case we want a quantile that accumulates \alpha/2 of the area on the tails of the normal standard distribution, and for this case we can calculate the z value with the following excel codes:

"=NORM.INV(alpha/2,0,1)"

"=NORM.INV(alpha/2,0,1)"

c) For this case we want to find a value of z that satisfy:

P(Z > z_alpha) = 0.05.

And we can use the following excel code:

"=NORM.INV(0.95,0,1)"

And we got z_{\alpha/2}=1.64

Step-by-step explanation:

Previous concepts

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 Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Solution to the problem

Part a

P(-z_0.025 < Z < z_0.025)

For this case we want a quantile that accumulates 0.025 of the area on the tails of the normal standard distribution, and for this case we can calculate the z value with the following excel codes:

"=NORM.INV(0.025,0,1)"

"=NORM.INV(0.025,0,1)"

And for this case the two values are :z_{crit}= \pm 1.96

Part b

P(-z_{\alpha/2} < Z < z_{\alpha/2})

For this case we want a quantile that accumulates \alpha/2 of the area on the tails of the normal standard distribution, and for this case we can calculate the z value with the following excel codes:

"=NORM.INV(alpha/2,0,1)"

"=NORM.INV(alpha/2,0,1)"

Part c

For this case we want to find a value of z that satisfy:

P(Z > z_alpha) = 0.05.

And we can use the following excel code:

"=NORM.INV(0.95,0,1)"

And we got z_{\alpha/2}=1.64

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The first thief takes (1/2 x + 1) .  What remains ?   x - (1/2x + 1)

So the 2nd thief takes  2/3 of  [  x - (1/2x + 1) ]

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So the 3rd thief takes    2/3 of  { x - 2/3 [ x - (1/2x + 1) ] }  and he takes 1 more .

   What remains ?    x - ( 2/3 { x - 2/3 [ x - (1/2x + 1) ] } + 1 )

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===============================================
This is a lot harder than just solving the problem with logic and
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Start from the end and work backwards:

-- One diamond is left.
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So he found 6 when he arrived.
-- 6 was 1/3 of what was there before the second thief helped himself.
So there were 18 when the 2nd man arrived.
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Thank you for your generous 5 points.


 
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