That do not make no sense to me.
Repeat question, from the way I understand it, the answer is impossible.
Thus probability of getting a hotel is .85 and you want to have such as probability at least one is .95 or more. If you have what is the probability that you do not get a room? Well, each one is .15 and there are thus the probability is OF GETTING AT LEAST ONE ROOM, isOriginally Posted by magicpunt
and you want that . Thus,
Thus,
Thus,
Make chart, for values,
Note at we have already it less than .05
However, I am sure if this is what you mean.
I appreciate the help but let me rephrase.
You are the hotel manager. You have 300 hotel rooms in your hotel. There is an 85% chance that those who book a room will actually show up and a 15% chance that they will not (thus the room is "booked" but not used).
You want to book as many rooms as possible so that there is a 95% chance that all of those who book with you will have a room (a 95% confidence that you won't be overbooked).
Let P(N|M) be the probability that there are exactly N shows out of M bookings.Originally Posted by magicpunt
Then the question is:
What is the largest M such that
P=P(0|M)+P(1|M) + P(2|M) + .. + P(300|M)>=0.95 ?
(that is: what is the maximum number of bookings M so that there is less
than a 5% chance of more than 300 shows?).
RonL
If the manager books rooms, the number of rooms taken will have a binomial distribution with probability of success and number of trials You want to know what is the highest value of that leaves a .95 probability that the number of rooms taken is no more than 300. Since calculating that probability from the binomial distribution is messy and probably not intended by your instructor, you should use the normal approximation to the binomial distribution.Originally Posted by magicpunt
Treat the number of rooms taken as a normal variable with mean and standard deviation Find the maximum with the probability Can you take it from here?
Thank you, Captain! Confusing the standard deviation of which is with the standard deviation of which is as you say, is a common mistake for me and it seems it's not the last time I'll make it. When working this kind of problem, I'll check whether the results are reasonable, and then have to go back and make that correction.Originally Posted by CaptainBlack
As for the continuity correction, there ain't no stinking continuity correction in the Central Limit Theorem!