Joint PMF of Rolling a 6-Sided Die 5 Times

In summary, the joint PMF for rolling a 6-sided die 5 times and having Event X be when a 1, 2, or 3 shows up and Event Y be when a 4 or 5 shows up is given by P(X=x,Y=y)=P(x)p(y|x)=(5Cx)(0.5^5)*((5-x)Cy)((1/3)^y)((2/3)^(5-x-y)), where X~Bin(5,0.5) and Y~Bin(5-x,2/3). This can also be represented as a trinomial distribution with P\{X = x, Y = y, Z = 5-x-y
  • #1
joemama69
399
0

Homework Statement



Roll a 6-sided die 5 times. Event X is when a 1,2,3 shows up. Event Y is when 4,5 show up. Show the joint PMF.


Homework Equations





The Attempt at a Solution



So... here is where I am at...

X~Bin(5,0.5) & Y~Bin(5,1/3)

P(X=x)=(5 C x)(.5^5) & P(Y=y)=(5 C y)(1/3)^y (2/3)^(5-y)

Also the events are dependent... which is where my confusion comes from

Originaly I did not realize it was dependant and I found all the joint probabilities by doing p(x,y)=p(x)p(y), but this is not correct because you cannot have X=4 & Y=3

Then I tried conditional probabilitys...

P(X=x,Y=y) = P(x)*P(y|x)=(5 C x)(.5^5)*((5-x) C y)(1/3)^y (2/3)^(5-y)

but this is not working out either. What am I doing wrong. Am I missing something?
 
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  • #2
joemama69 said:

Homework Statement



Roll a 6-sided die 5 times. Event X is when a 1,2,3 shows up. Event Y is when 4,5 show up. Show the joint PMF.

Homework Equations


The Attempt at a Solution



So... here is where I am at...

X~Bin(5,0.5) & Y~Bin(5,1/3)

P(X=x)=(5 C x)(.5^5) & P(Y=y)=(5 C y)(1/3)^y (2/3)^(5-y)

Also the events are dependent... which is where my confusion comes from

Originaly I did not realize it was dependant and I found all the joint probabilities by doing p(x,y)=p(x)p(y), but this is not correct because you cannot have X=4 & Y=3

Then I tried conditional probabilitys...

P(X=x,Y=y) = P(x)*P(y|x)=(5 C x)(.5^5)*((5-x) C y)(1/3)^y (2/3)^(5-y)

but this is not working out either. What am I doing wrong. Am I missing something?

I don't like your labelling of X the as occurrence of {1,2,3}. Instead, let X = number of tosses resulting in {1,2,3} and let Y = number of tosses resulting in {4,5}. So, X~Bin(5,1/2), and for each x ε {0,1,2,3,4,5}, Y|X=x is Bin(5-x,1/3).

Alternatively, you can say that Y ~ Bin(5,1/3) and for each y ε {0--5}, X|Y=y is Bin(5-y,1/2).

Either way, you can get p(x,y). It might prove instructive to show that both ways give you the same p(x,y).
 
Last edited:
  • #3
Ya I kinda short handed the problem. But so your saying I have the correct formula? Because when I applied it I didn't get a sum of marginal probabilities equal to 1. I even used excel to make sure there was not an error in arithmetic.
 
  • #4
joemama69 said:
Ya I kinda short handed the problem. But so your saying I have the correct formula? Because when I applied it I didn't get a sum of marginal probabilities equal to 1. I even used excel to make sure there was not an error in arithmetic.

You write "so your saying I have the correct formula?" I said nothing of the sort, and I don't know why you think I did. Read my posting again!
 
  • #5
Ok so I tried to find it both ways but got different answers...

X~B(5,0.5), Y~ B(5-x,1/3), p(x,y)=p(x)p(y|x)=(5Cx)(0.5^5)*((5-x)Cy)((1/3)^y)((2/3)^(5-x-y))

... I thought this was the correct answer because all the marginal probabilities did sum to 1. But my professor disagreed.

so I tried ...
X~B(5-y,0.5), Y~ B(5,1/3), p(x,y)=p(y)p(x|y)=(5Cy)((1/3)^y)((2/3)^(5-y)*((5-y)Cx)((1/2)^x)(1/2)^(5-y-x))

... but did not get a sum of probabilities =1.

Are my formulas still wrong?
 
  • #6
joemama69 said:
Ok so I tried to find it both ways but got different answers...

X~B(5,0.5), Y~ B(5-x,1/3), p(x,y)=p(x)p(y|x)=(5Cx)(0.5^5)*((5-x)Cy)((1/3)^y)((2/3)^(5-x-y))

... I thought this was the correct answer because all the marginal probabilities did sum to 1. But my professor disagreed.

so I tried ...
X~B(5-y,0.5), Y~ B(5,1/3), p(x,y)=p(y)p(x|y)=(5Cy)((1/3)^y)((2/3)^(5-y)*((5-y)Cx)((1/2)^x)(1/2)^(5-y-x))

... but did not get a sum of probabilities =1.

Are my formulas still wrong?

Sorry: I tried to edit my previous posting but the system would not let me, and so I decided to wait until you responded before posting a new response (not being sure if you had or had not abandoned the topic).

I made a blunder before. Given {X=x}, the remaining tosses must result in outcomes {4,5,6}, and so the conditional probability governing Y is 2/3 (must get 4 or 5 from 4,5,6). That is, Y|X=x ~ bin(5-x,2/3). Similarly, X|Y=y ~ bin(5-y,3/4).

If you know about the multinomial distribution, this problem involves the trinomial case, because if we have {X=x, Y=y}, there must be Z = 5-x-y outcomes from the third set {6}. So we really have trinom(5;1/2,1/3,1,6):
[tex] P\{X = x, Y = y\} = P\{X = x, Y = y, Z = 5-x-y\} = {5 \choose x, y, 5-x-y} (1/2)^x(1/3)^y (1/6)^{5-x-y}. [/tex]
Here
[tex] {n \choose a,b,c} = \frac{n!}{a! b! c!}[/tex]
is the trinomial coeffcient.
 
  • #7
ok thanks, I finally got it right... Thank you
 

Related to Joint PMF of Rolling a 6-Sided Die 5 Times

1. What is the joint probability mass function (PMF) of rolling a 6-sided die 5 times?

The joint PMF of rolling a 6-sided die 5 times is a function that describes the probability of obtaining a specific combination of outcomes when rolling the die 5 times. It takes into account the probabilities of each individual roll as well as the order in which they occur.

2. How is the joint PMF calculated?

The joint PMF is calculated by multiplying the individual probabilities of each roll. For example, if the probability of rolling a 3 on the first roll is 1/6, the probability of rolling a 5 on the second roll is also 1/6, and so on, the joint PMF for rolling a 3, 5, 2, 4, and 6 in that order would be (1/6)*(1/6)*(1/6)*(1/6)*(1/6) = 1/7776.

3. What are the possible outcomes when rolling a 6-sided die 5 times?

There are 6 possible outcomes for each roll of the die (1, 2, 3, 4, 5, or 6), and since we are rolling the die 5 times, there are 6^5 = 7776 possible combinations of outcomes. This means that there are 7776 possible outcomes when rolling a 6-sided die 5 times.

4. How does the joint PMF of rolling a 6-sided die 5 times differ from the individual probabilities of each roll?

The joint PMF takes into account the order in which the outcomes occur, while the individual probabilities only consider the probability of obtaining a specific outcome on a single roll. For example, the probability of rolling a 3 on the first roll and a 5 on the second roll is different from the probability of rolling a 5 on the first roll and a 3 on the second roll, even though both combinations have the same individual probabilities.

5. What other factors can affect the joint PMF of rolling a 6-sided die 5 times?

The joint PMF can also be affected by any external factors that may influence the outcome of the rolls, such as the surface the die is being rolled on, the force of the roll, or the temperature of the environment. These factors can alter the individual probabilities and therefore affect the joint PMF.

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