Calculating Joint Probability Mass Function for Two Dice Toss

In summary: It seems to me that you are making a big mess of something that is trivial. It is a simple matter of counting. Nothing more. The sample space is of size 21. This has nothing to do with probabilities or random variables. That's simple the number... It seems to me that you are making a big mess of something that is trivial. It is a simple matter of counting. Nothing more.
  • #1
r0bHadz
194
17

Homework Statement


Two dice are tossed. Let X be the smaller number of points. Let Y be the larger number
of points. If both dice show the same number, say, z points, then X = Y = z.

Homework Equations

The Attempt at a Solution


Find the joint probability mass function (X,Y)

For (1,1) = 1/36, I do not understand why every other vector, say (1,2) does not = 1/36
 
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  • #2
I'm pretty sure it has to do with introducing a random variable P = sum of the two rolls but I don't see why this would be necessary. If you roll two dice I don't see why they wouldn't be independent. So the sample space has a size of 36, each of the 36 are equally likely, P(1,1) should = P(1,2)
 
  • #3
Hmm I think I'm getting closer. Since x is less than or = to y, the probability changes. so for the row of x values, where y = 1, you have 5 0's, This is different from the sample space which has 36 entries
 
  • #4
r0bHadz said:

Homework Statement


Two dice are tossed. Let X be the smaller number of points. Let Y be the larger number
of points. If both dice show the same number, say, z points, then X = Y = z.

Homework Equations

The Attempt at a Solution


Find the joint probability mass function (X,Y)

For (1,1) = 1/36, I do not understand why every other vector, say (1,2) does not = 1/36

You mean that ##P(1, 2) = P(2, 1) = 1/36## etc.?
 
  • #5
r0bHadz said:

Homework Statement


Two dice are tossed. Let X be the smaller number of points. Let Y be the larger number
of points. If both dice show the same number, say, z points, then X = Y = z.

Homework Equations



The Attempt at a Solution


Find the joint probability mass function (X,Y)

For (1,1) = 1/36, I do not understand why every other vector, say (1,2) does not = 1/36
r0bHadz said:
Hmm I think I'm getting closer. Since x is less than or = to y, the probability changes. so for the row of x values, where y = 1, you have 5 0's, This is different from the sample space which has 36 entries
You have left out enough detail so that we are left to guessing just what difficulties you are having .

You say the probability for (1,2) is not 1/36, but don't say what it is. My guess is that it's 1/18. Is that correct?
 
  • #6
PeroK said:
You mean that ##P(1, 2) = P(2, 1) = 1/36## etc.?
yes. I don't see why not.
 
  • #7
SammyS said:
You have left out enough detail so that we are left to guessing just what difficulties you are having .

You say the probability for (1,2) is not 1/36, but don't say what it is. My guess is that it's 1/18. Is that correct?
Yes its 1/18.. I think I'm starting to understand now. It's not dice X and dice Y, it is high score and low score. I think my difficulty came from my lack of understanding of what a random variable is.
 
  • #8
r0bHadz said:
yes. I don't see why not.

##P(2, 1) = 0##, as it is stated in the problem that ##X \le Y##. If you roll ##1## and ##2##, then ##X## is always counted as ##1##.

It doesn't have anything to do with random variables, as such. For example, if you have a table headed ##X## and ##Y##, then you would never have an entry ##2, 1##. You would always enter that as ##1, 2##.

This is quite important, because you often record data in ascending or descending sequence. E.g. the lottery. I.e. you order or sort the data before you record it.
 
  • #9
PeroK said:
##P(2, 1) = 0##, as it is stated in the problem that ##X \le Y##. If you roll ##1## and ##2##, then ##X## is always counted as ##1##.

It doesn't have anything to do with random variables, as such. For example, if you have a table headed ##X## and ##Y##, then you would never have an entry ##2, 1##. You would always enter that as ##1, 2##.

This is quite important, because you often record data in ascending or descending sequence. E.g. the lottery. I.e. you order or sort the data before you record it.

Right, so because there are 2 ways you can get (1,2) you have 2(1/36) = 1/18. So I was wrong in my the first post after my OP, you do not need to introduce a new random variable, and the sample space is of size 36.
 
  • #10
r0bHadz said:
Right, so because there are 2 ways you can get (1,2) you have 2(1/36) = 1/18. So I was wrong in my the first post after my OP, you do not need to introduce a new random variable, and the sample space is of size 36.

The sample space is of size 21. This has nothing to do with probabilities or random variables. That's simple the number of pairs ##(X, Y)##, where ##X \le Y##.
 
  • #11
r0bHadz said:
Yes its 1/18.. I think I'm starting to understand now. It's not dice X and dice Y, it is high score and low score. I think my difficulty came from my lack of understanding of what a random variable is.

I think it is more your not acknowledging the importance of understanding what the sample space is. You can have lots of probability problems that do not involve random variables, but require knowing what is the sample space is of major importance. In terms of sample spaces, we have in this problem:
$$
\begin{array}{cc|cc}
\text{die 1}&\text{die 2}& \text{low} & \text{high}\\ \hline
1 & 1 & 1 & 1 \\
1 & 2 & 1 & 2 \\
2 & 1 & 1 & 2 \\
\vdots & \vdots & \vdots & \vdots \\
4 & 6 & 4 & 6 \\
6 & 4 & 4 & 6 \\
\vdots & \vdots & \vdots & \vdots\\
6 & 6 & 6 & 6
\end{array}$$
So, for example, P(low=4,high=6) = P(d1=4,d2=6)+P(d1=6,d2=4) = 2/36.
 
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  • #12
That makes sense. For any probability problem, before I do anything, I think I should completely understand the sample space before even attempting the problem. Your post has answered my question, thanks man.
 
  • #13
But to nit pick a bit, you also need to specify what aspect of a situation you are observing. Here you throw dice and observe the face facing you. Pedantic here, but helpful in situations where it is not so obvious what you are keeping track of.
 

1. What is a joint probability problem?

A joint probability problem is a type of statistical problem that involves calculating the probability of two or more events occurring simultaneously. It is often used in fields such as mathematics, economics, and engineering to analyze the likelihood of multiple events happening together.

2. How is joint probability different from conditional probability?

Joint probability and conditional probability are both ways of calculating the likelihood of events, but they differ in their approach. Joint probability looks at the probability of two or more events happening together, while conditional probability looks at the probability of one event happening given that another event has already occurred.

3. What is the formula for calculating joint probability?

The formula for joint probability is P(A and B) = P(A) * P(B|A), where P(A) represents the probability of event A occurring, P(B) represents the probability of event B occurring, and P(B|A) represents the probability of event B occurring given that event A has already occurred.

4. How do you interpret the results of a joint probability problem?

The results of a joint probability problem can be interpreted as the likelihood of two or more events happening together. For example, if the joint probability of event A and event B is 0.25, it means that there is a 25% chance of both event A and event B occurring at the same time.

5. What are some real-world applications of joint probability?

Joint probability has many real-world applications, such as predicting the outcome of sporting events, analyzing the success of marketing campaigns, and assessing the risk of multiple events happening in the stock market. It is also used in medical research to analyze the likelihood of multiple risk factors contributing to a disease or condition.

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