Impossible Statistics/Probability Questions

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Customers arrive at a checkout counter at a department store an average of 8 times per hour. Twenty percent of them are buying things from section A of the store.

a) Find the probability of getting fewer than seven customers at the checkout counter in one hour.

How are supposed to know? There is a table in the back of the book that we can use to look stuff up, but I don't really understand it. I am not even sure if that's what I need, but this question seems impossible.

b) Find the probability of getting fewer than seven customers at checkout counter for seven of the next 10 hours.

Still have no idea

c) Find the probability of having at least seven customers arrive at the checkout counter before a customer buying things from section A arrives at the checkout counter.

Seems possible...negative binomial distribution?

d) From 80 purchases made at the checkout counter, suppose that 21 were from section A. An auditor samples 10 purchases, find the probability that 5 of them are from section A.

Hypergeometric?
 
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a) if by the table you mean a table of z-scores and areas under the normal distrobution curve and such, those are useless unless you knew the standard deviation of the data. There is nothing you can do with just the mean.

b)you would use the answer from (a) and the cumulative binomial probability formula

c) probability of atleast seven + probability of less than 7 = 1

d) another binomial probability question.
 
a) The table says "Critical Values for T Distributions"...don't really know what that is.

b) Is (a) even possible to figure out?

c) Yeah, but I don't know the probability of less than 7. Isn't the negative binomial the thing that counts the number of failures to get a success?...Oh wait, would that mean potentially an infinite amount of failures? Is it binomial instead of negative binomial?

d) It isn't hypergeometric?
 
Yes, (a) is possible to figure out. It's a rather straightforward task too, once you've modeled the problem at hand.
 
gah, I wish I got to edit my post before someone pointed out my error
 
Hurkyl said:
Yes, (a) is possible to figure out. It's a rather straightforward task too, once you've modeled the problem at hand.
I still don't get it. Want to give me a hint?
 
Poisson Distribution
 
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