Not sure what i did wrong binomial probability

AI Thread Summary
In a 22-item true-false exam, the probability of a student passing by guessing is calculated using binomial probability. To determine the likelihood of passing with at least 14 correct answers, one must sum the probabilities from 14 to 22 correct answers. An online calculator can simplify this process, or a Normal approximation can be used, yielding a probability of approximately 0.1004 compared to the exact binomial probability of 0.1431 for 14 correct answers. The discussion highlights the importance of understanding both exact calculations and approximations, especially for small sample sizes. Ultimately, while approximations can be useful, exact calculations are preferred for accuracy in critical scenarios.
mtingt
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In a 22-item true–false examination, a student guesses on each question.

If 14 correct answers constitute a passing grade, what is the probability the student will pass?

i did c(22,14)* (1/2)^14 * (1/2)^8
 
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You have to add in the probabilities for more than 14 correct guesses. Your answer is for exactly 14 correct.
 
so i would have to add every single probability up to 22?
is there any other way i could do this?
 
mtingt said:
so i would have to add every single probability up to 22?
is there any other way i could do this?

You can use an online calculator for p=0.5, n=22, x=14 and solve for P(X\geq x)

http://stattrek.com/Tables/Binomial.aspx
 
mtingt said:
so i would have to add every single probability up to 22?
is there any other way i could do this?
You might also use a Normal approximation to the Binomial distribution.
 
awkward said:
You might also use a Normal approximation to the Binomial distribution.

The normal approximation gives p=0.1004 whereas the presumably exact binomial gives (P(X\geq x)=0.1431 for x=14.

For the normal approximation I'm using mean 11 and SD = \sqrt {11(1-0.5)} = 2.345
 
SW VandeCarr said:
The normal approximation gives p=0.1004 whereas the presumably exact binomial gives (P(X\geq x)=0.1431 for x=14.

For the normal approximation I'm using mean 11 and SD = \sqrt {11(1-0.5)} = 2.345
I get P(X \geq 13.5) = 0.1432 using the Normal distribution adjusted for continuity.
 
awkward said:
I get P(X \geq 13.5) = 0.1432 using the Normal distribution adjusted for continuity.

I did too, but when Ted Williams was told his 0.3995 batting average would go into the record books as 0.400, he said that wasn't really 0.400 and played through two final season games ending up with a 0.406 batting average. Is 13.5 a passing grade or is 14 a threshold value? I understand the continuity correction and it's fine for some applications but for n=22 and a "threshold" value, why not use an exact calculation? In either case, you will likely use tables or a calculator.

Having said that, it's closer than I would have thought, but I wouldn't have been comfortable without doing the exact approach.
 
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I agree, in this case the approximation works better than we have any right to expect. Still, it's a useful tool to have around.
 
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