Probability: joint probability distribution problem?

In summary, the problem involves John and George meeting each other at a set time, with John waiting for George for 15 minutes and George waiting for John for 5 minutes. The probability of an encounter is found by considering the variable T, which is the difference between George's arrival time and John's arrival time. The range of values for T in which an encounter will occur is between -15 minutes and 5 minutes, and the probability is determined by finding the probability density function of T.
  • #1
libelec
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Homework Statement


John and George are set to meet each other at 12 o'clock. John's time of arrival, J, is distributed uniformly between 12:00 and 12:15. John will wait for George for 15 minutes. If he doesn't show up, he leaves. George's time of arrival, G, is also uniformly distributed, between 12:05 and 12:20. But he will only wait 5 minutes for John.

Find the probability of an encounter.

The Attempt at a Solution



I'm at complete lost with this problem. I think that what I have to do is find the jount probability distribution of J and G, but I couldn't say why. And the "waits for 15 minutes" thing also confuses me.

Any ideas?
 
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  • #2
Anybody?
 
  • #3
Hint: Let T=G-J. For what range of values of T will an encounter happen?
 
  • #4
T between 0:00 and 0:05...

OK, and I have to do the same thing but considering T2 = J-G. How can I then find the entire answer? T+T2?
 
  • #5
Note that T2 = -T, so it's essentially the same variable. In other words, if you have something like a<T2<b, that's the same as -a>T>-b. You only have to work with one variable. There's no need to work the cases out separately and combine them at the end.
 
  • #6
No, no, I see. T has to be between -0:15 and 0:05, right? Because if G<J, T<0, and since J can only be 15 minutes earlier than G otherwise he leaves, T> -0:15. and if G>J, T>0, and since G can only be 5 minutes earlier than J, T<0:05.

So, what I'm looking for is P(-0:15<= T <= 0:05), right?
 
  • #7
Right!
 
  • #8
OK, thanks.
 
  • #9
All understood.. but how to find out the p.d.f of T? Because without the pdf of T the required probability cannot be calculated..

Please help
 

1. What is a joint probability distribution?

A joint probability distribution is a statistical representation of the simultaneous probabilities of two or more random variables. It shows the likelihood of different outcomes occurring when multiple variables are involved.

2. How is joint probability calculated?

Joint probability is calculated by multiplying the individual probabilities of each variable. For example, if the probability of event A is 0.5 and the probability of event B is 0.3, then the joint probability of both events occurring is 0.5 x 0.3 = 0.15.

3. What is the difference between joint probability and conditional probability?

Joint probability involves the simultaneous occurrence of two or more events, while conditional probability looks at the probability of one event occurring given that another event has already occurred. Joint probability can be used to calculate conditional probability, but they are not the same thing.

4. How is joint probability used in real-life scenarios?

Joint probability is used in many real-life scenarios, such as in risk analysis, market research, and medical studies. It can help determine the likelihood of certain outcomes and make informed decisions based on the probabilities.

5. Can joint probability be greater than 1?

No, joint probability cannot be greater than 1 as it represents the likelihood of events occurring together. The total probability of all possible outcomes cannot exceed 1, as it represents 100% of all possible events.

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