Probability Mass Function

In summary, to meet the goal of serving at least 95% of people who want tickets, the probability of getting through to the ticket agency on each call must be at least 0.95.
  • #1
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Homework Statement


You are a manager of ticket agency that sells concert tickets. You assume that people will call 3 times in an attempt to buy the ticket and give up. You want to make sure that you are able to serve at least 95% of the people who wants tickets. Let p be the probability that a caller gets through to your ticket agency. What is the minimum value of p necessary to meet your goal?


Homework Equations


Theorem of Probability Mass Function


The Attempt at a Solution


So there are three independent outcome. Let X be the random variable for the corresponding three events, and let S denote the successful purchase of the ticket and F the failure case.

{X = 0} = {S} / Successful in first call
{X = 1} = {FS} / Successful in second call
{X = 2} = {FFS} / Successful in third call
{X = 3} = {FFF} / No Ticket purchase

I'm completely stuck here. Frankly, I don't even know if I'm approaching this problem correctly. Any help will be appriciated.
 
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  • #2
If p is the probabality a caller gets through on each call,(1) what is the probability that the caller gets through the first time?

(2) what is the probability that the caller gets through the second time?

(3) what is the probability that the caller gets through the third time?

(4)what is the total probability?

Hint- for a caller to get through on the second call, he must have also failed to get through on the first call
 
  • #3
Ok. Obviously, the probability of getting the ticket on the first call is p.

Probability on the second one is 1-(1-p)^2 and the third one is 1-(1-p)^3

Then the total probability is p + (1-(1-p)^2) + (1-(1-p)^3)

Am I right? And from this, do I set the whole equation to 0.95 and solve for p? I don't quite understand the notion here
 
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  • #4
You're right on the first one, but not the next two...what is the probability of failing the first time?
 
  • #5
Probability of failing the first time is 1-p
 
  • #6
Right, so the probability of getting through the second time is equal to the probability of failing the first time AND succeeding the second {FS} so wouldn't that just be (1-p)p?

In other words F=1-p , S=p. What does that make the probability that a caller gets through on the 3rd attempt?
 
  • #7
oh ok, then the next event is {FFS] so it's (1-p)^2 * p for the third attempt.

Ok, then the total probability is p + p(1-p) + p(1-p)^2

So I set this expression equal to 0.95 and solve for p?
 
  • #8
Yup you got it, you want the total probabilty of {X=0}+{X=1}+{X=2} (as you have them labelled) to be at least 0.95, so just solve {X=0}+{X=1}+{X=2}=0.95.

Alternatively, you know that {X=0}+{X=1}+{X=2}+{X=3}=1 since the total probability of all possible outcomes must be 1. So you could have saved a little time by noting that {X=0}+{X=1}+{X=2}=1-{X=3} and just found {X=3}={FFF} and solved the equation 1-{FFF}=0.95. Either way you will get the same thing.
 
  • #9
Ahhhh! I should've noticed that earlier! I was like "I have to solve a third-order equation in a probability class??"

haha thanks a lot.
 
  • #10
l46kok said:
Ahhhh! I should've noticed that earlier! I was like "I have to solve a third-order equation in a probability class??"

haha thanks a lot.

No problem, but it is still a 3rd order equation you should get.
 

What is a Probability Mass Function?

A Probability Mass Function (PMF) is a function that maps the possible values of a discrete random variable to their corresponding probabilities. It is used to describe the probability distribution of a discrete random variable.

What are the main properties of a Probability Mass Function?

The main properties of a Probability Mass Function include:
- The PMF must be non-negative for all values of the random variable.
- The sum of all probabilities in the PMF must equal 1.
- The PMF can only take on discrete values, meaning the random variable can only have a finite or countably infinite number of outcomes.
- The PMF can be used to calculate the probability of a specific outcome or a range of outcomes.

How is a Probability Mass Function different from a Probability Density Function?

A Probability Mass Function is used for discrete random variables, while a Probability Density Function is used for continuous random variables. This means that the PMF gives the probability of specific values, while the PDF gives the probability of a range of values. Additionally, the PMF is defined as a function, while the PDF is defined as a curve.

What is the relationship between a Probability Mass Function and a Cumulative Distribution Function?

The Cumulative Distribution Function (CDF) is the sum of all probabilities in the PMF up to a certain value of the random variable. In other words, the CDF gives the probability that the random variable is less than or equal to a specific value. The CDF is the integral of the PMF, and the PMF can be obtained by differentiating the CDF.

How is a Probability Mass Function used in statistical analysis?

A Probability Mass Function is used to describe the probability distribution of a discrete random variable. This allows us to calculate probabilities of specific outcomes or ranges of outcomes, which is essential in making statistical inferences and predictions. The PMF is also used in hypothesis testing, where it helps determine the likelihood of obtaining a particular sample from a population with a known PMF.

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