How can I solve this uniform distribution question?

In summary, the question asks for the approach to solving a conditional probability question involving a random quantity X representing the time spent in a queue, with given probabilities and a known time already spent. The solution involves finding P{X > 8}/P{X >= 5} and understanding the value of X in relation to the given information.
  • #1
jsmith613
614
0

Homework Statement


http://www.xtremepapers.com/Edexcel/Advanced%20Level/Mathematics/Subject%20Sorted/S2/S2%202008-06.pdf

Question 1(d)

Homework Equations



The Attempt at a Solution


So I know this is a conditional probability question.
Now I would have said
P(X>8) / P(X=5)
because it is probability I will NOT be served (i.e: time is greater than 8 mins) given I have already waited 5 mins
this gives me infinity because x/0 = inifinty

How do I approach this question?
 
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  • #2
jsmith613 said:

Homework Statement


http://www.xtremepapers.com/Edexcel/Advanced%20Level/Mathematics/Subject%20Sorted/S2/S2%202008-06.pdf

Question 1(d)

Homework Equations



The Attempt at a Solution


So I know this is a conditional probability question.
Now I would have said
P(X>8) / P(X=5)
because it is probability I will NOT be served (i.e: time is greater than 8 mins) given I have already waited 5 mins
this gives me infinity because x/0 = inifinty

How do I approach this question?

No: because she has already waited 5 minutes, we know that X >= 5. You need P{X > 8}/P{X >= 5}.

RGV
 
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  • #3
see that's the prob I can't see why its x≥5 because she has waited 5 mins (x=5)
X = the amount of time Jean waits in the queue?
 
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  • #4
jsmith613 said:
see that's the prob I can't see why its x≥5 because she has waited 5 mins (x=5)
X = the amount of time Jean waits in the queue?

X = amount of time that Jean would spend in the queue if she did not have to leave before being served; this is the random quantity representing the times she did spend in the queue on every day in the past. So, X is uniform from 0 to 10. On this one occasion we observe that after 5 minutes she is still in the queue, so on this one occasion, X >= 5. (X is not exactly equal to 5, because if it was she would not need to wait any longer; and, of course, X is not less than 5.) On this one occasion, the amount of time she spends in the queue is X (if X <= 8) and is 8 (if X > 8).
 
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What is a uniform distribution?

A uniform distribution is a probability distribution in which every possible outcome has an equal chance of occurring. This means that all values within a given range are equally likely to be observed.

What are the characteristics of a uniform distribution?

The main characteristics of a uniform distribution include a constant probability density function, a flat line on a graph, and a symmetrical shape. It also has a mean and median that are equal, and a standard deviation that is equal to the range divided by the square root of 12.

What is the purpose of using a uniform distribution?

A uniform distribution is often used in statistical analysis and modeling because it is easy to work with and makes fewer assumptions about the data compared to other distributions. It is also useful for generating random numbers within a given range.

How is a uniform distribution different from a normal distribution?

A uniform distribution is different from a normal distribution in that it has a constant probability density function, while a normal distribution has a bell-shaped curve. Additionally, a normal distribution assumes that the data is normally distributed, while a uniform distribution does not make any assumptions about the data.

How do you calculate probabilities with a uniform distribution?

To calculate probabilities with a uniform distribution, you divide the number of outcomes of interest by the total number of possible outcomes. This will give you the probability of a specific value occurring within the given range. For example, if you roll a fair die (with 6 sides) and want to know the probability of rolling a 3, it would be 1/6 since there is only one outcome of interest (rolling a 3) out of six possible outcomes (rolling a 1, 2, 3, 4, 5, or 6).

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