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#2 |
The Maintenance Guy
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48÷2(9+3)
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#3 |
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#4 |
Hey Loochy, I'm hooome!
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Ask Frankie. He has a super IQ and he knows everything.
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#5 |
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I came up with 16 rolls. At 2.57 standard deviations, on a standard bell curve, there is a 99% probability a given outcome would be expected. If there is a 25% chance that a number would appear (four sided die), wouldn't that mean that there is a 75% chance that that one of the other numbers appears-- and that there is a 75% chance on each successive roll that one of the other numbers appear?
In other words, .75 x .75 x .75...until there is only a .01 probability that the next roll will be one of the three numbers without the original number being rolled? Does that make sense? Am I completely off base? |
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#6 | |
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Quote:
The problem involves a discrete distribution that puts 25% probability on each of the integers from 1 to 4. The course materials should have provided you a formula for computing the standard deviation for such a distribution, right? If you were to plot the density of that distribution, you will see that it looks nothing like a normal curve. Instead, the distribution puts the same amount of weight on each of only 4 points. You can compute the standard deviation for the problem's discrete uniform distribution using the formula you have for a standard deviation for a discrete probability distribution. (Alternatively, you can simply use one of the two Excel's functions for calculating POPULATION standard deviations and apply that to the four integers, like this: =stdevp(1,2,3,4) ) If you do that, you will learn what the population standard deviation is for that distribution. Once you know that, then you just need to compute what 2.57 of those standard deviations would equal. Then you just need to find the next greatest integer, aka the ceiling, aka the minimum integer whose value is at least as big as 2.57 * SD, where SD is the standard deviation whose value you computed at the beginning of the problem. If I'm interpreting that problem correctly, I suspect that the intent of the problem is to help the student get familiar with translating a word problem into a math problem and then apply concepts you learned early in the class about standard deviations and other parameters that describe key features of distributions. Hope this helps gets you started on the other problems! |
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#7 |
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42 rolls.
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#8 | |
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#9 | |
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#11 |
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18.41 rolls to be near 2.51 standard deviations--assuming a normal distribution
2.51 std deviations = ~.005 (half of a percent) I am reading the question as this: how many times would I have to roll the dice to be at 2.51 std devs for not seeing that number come up.. so .75% ^ x = .005 18.41 rolls in a row without N number showing up disclaimer: im drunk , tired and going to bed LOL
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#12 | |
Emporer of Mongo
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oh crap i dint read dan T's.......i guess it isnt a 'normal' distribution?
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---- 2018 Adopt-A-Chief : Chris Conley 2017 Adopt-A-Chief : FRANK ZOMBO Click here-->***The Holy Chiefsplanet Lexicon **** Last edited by Ming the Merciless; 08-03-2011 at 02:15 AM.. |
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#13 | |
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#14 |
Emporer of Mongo
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caught that 60 seconds b4 you posted, thx
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#15 |
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My best guess, given the wording, is that we are working with a geometric distribution with p=.25 and trying to determine the minimum number of trials it will take for a first success that occurs more than 2.57 standard deviation away from the mean. The mean for a geometric distribution is 1/p, so 1/.25=4. The variance is given by (1-p)/p^2 or .75/.0625=12. Thus the sd is 12^.5 or approximately 3.464. 2.57 sds is approximately equal to 8.9. So, to be at least 2.57 sds away from the mean you need at least 4 + 9 rolls, or 13.
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