Better way to do this probability problem?

But is there a way to apply the trinomial distribution to part b) as well? Or would I have to use a different method for that?In summary, we have a problem where we toss a fair die 4 times and let X and Y represent the number of times we get 1 or 2 and 3, 4, or 5 respectively. We are asked to find the probability of getting X=1 and Y=2, which is 1/6. To find the probability of X=Y, we use the trinomial distribution, which gives us a probability of 289/1296. We could also use the binomial distribution and consider all possible cases, which also gives us the same result.
  • #1
Gridvvk
56
1

Homework Statement


You toss a fair die 4 times. You let the random variable X denote the number of times a toss results in 1 or 2, and Y denote the number of time a toss results in 3,4, or 5.

a) Find P(X = 1, Y = 2)
b) Find P(X = Y)

Homework Equations


None that I know of.

The Attempt at a Solution


I defined a third r.v. Z := number of times a toss results in a 6.
X ~ Bin(4,1/3), Y~Bin(4,1/2), Z~Bin(4,1/6).

a) P(X = 1, Y = 2) = P(X = 1, Y=2, Z = 1) = (4 choose 1)(3 choose 1)(1/3)(1/2)^2(1/6) = 1/6

You needed to take the groupings into account. There are 12 such orderings, one being
XYYZ, my reasoning was there are (4 choose 1) ways to move that Z around, and (3 choose 1 ways) to move X in XYY, giving 4 * 3 = 12 different possibilities.

b) P(X = Y).
Case 1: X=Y=0, Z = 4
P(Case 1) = (1/6)^4

Case 2: X=Y=1, Z = 2
P(Case 2) = 2(4 choose 2)(1/3)(1/2)(1/6)^2 = 1/18
Where you have 12 orderings again here, one such is XYZZ, two ways to shift the XY, and (4 choose 2) ways to work with the ZZ.

Case 3: X = Y = 2, Z = 0.
P(Case 3) = (3 choose 1)(2 choose 1)(1/3)^2(1/2)^2 = 1/6

Where you have 6 groupings, one such is XXYY, my reasoning was you can move the second X in XYY (3 choose 1) ways and the outer X would then have (2 choose 1) ways.

So I got P(X = Y) = P(Case 1) + P(Case 2) + P(Case 3) = 289 / 1296.

-----------------------------------
I think my answer is correct (I could be wrong though). However, is there a better way to do this problem using our knowledge that X,Y, and Z are binomial? I only ask because I was a bit uncertain on the number of arrangements and just did it solely on intuition and oftentimes enumerated all possibilities to see if I was correct, so is there a better way to count the number of possibilities as well?
 
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  • #2
Gridvvk said:

Homework Statement


You toss a fair die 4 times. You let the random variable X denote the number of times a toss results in 1 or 2, and Y denote the number of time a toss results in 3,4, or 5.

a) Find P(X = 1, Y = 2)
b) Find P(X = Y)


Homework Equations


None that I know of.


The Attempt at a Solution


I defined a third r.v. Z := number of times a toss results in a 6.
X ~ Bin(4,1/3), Y~Bin(4,1/2), Z~Bin(4,1/6).

a) P(X = 1, Y = 2) = P(X = 1, Y=2, Z = 1) = (4 choose 1)(3 choose 1)(1/3)(1/2)^2(1/6) = 1/6

You needed to take the groupings into account. There are 12 such orderings, one being
XYYZ, my reasoning was there are (4 choose 1) ways to move that Z around, and (3 choose 1 ways) to move X in XYY, giving 4 * 3 = 12 different possibilities.

b) P(X = Y).
Case 1: X=Y=0, Z = 4
P(Case 1) = (1/6)^4

Case 2: X=Y=1, Z = 2
P(Case 2) = 2(4 choose 2)(1/3)(1/2)(1/6)^2 = 1/18
Where you have 12 orderings again here, one such is XYZZ, two ways to shift the XY, and (4 choose 2) ways to work with the ZZ.

Case 3: X = Y = 2, Z = 0.
P(Case 3) = (3 choose 1)(2 choose 1)(1/3)^2(1/2)^2 = 1/6

Where you have 6 groupings, one such is XXYY, my reasoning was you can move the second X in XYY (3 choose 1) ways and the outer X would then have (2 choose 1) ways.

So I got P(X = Y) = P(Case 1) + P(Case 2) + P(Case 3) = 289 / 1296.

-----------------------------------
I think my answer is correct (I could be wrong though). However, is there a better way to do this problem using our knowledge that X,Y, and Z are binomial? I only ask because I was a bit uncertain on the number of arrangements and just did it solely on intuition and oftentimes enumerated all possibilities to see if I was correct, so is there a better way to count the number of possibilities as well?

Both of your answers are correct. You could have saved a bit of time by using the trinomial distribution: if each 'trial' results in either outcomes A, B or C with respective probabilities ##p_A,\: p_B, \: p_C \; (p_A + p_B + p_C = 1)##, then for n independent trials, we have
[tex] P\{ N_A = a, N_B = b, N_C = c\}
= \frac{n!}{a! \: b! \: c!}\, p_A^a \, p_B^b \, p_C^c[/tex]
where ##a+b+c=n##.

You can easily derive this by successive application of the binomial:
[tex] P\{N_A=a, N_B=b, N_C=c \} = P\{N_A=a\} P\{N_B=b, N_C=c | N_A = a\}.[/tex]
We have
[tex] P\{N_A=a\} = {n \choose a} p_A^a \; (p_B + p_C)^{n-a},[/tex]
and
[tex] P\{N_B=b, N_C=c | N_A = a\} = {n-a \choose b} q_B^b \, q_C^c,[/tex]
where
[tex] q_B = P\{B| B \text{ or }C\} = \frac{p_B}{p_B + p_C} \\
q_c = P\{C| B \text{ or }C\} = \frac{p_C}{p_B + p_C}.[/tex]
If you put all these together you get the trinomial formula.
 
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  • #3
Gridvvk said:

Homework Statement


You toss a fair die 4 times. You let the random variable X denote the number of times a toss results in 1 or 2, and Y denote the number of time a toss results in 3,4, or 5.

a) Find P(X = 1, Y = 2)
b) Find P(X = Y)


Homework Equations


None that I know of.

I haven't worked your problem, but you can use the trinomial distribution:$$
P(X=x,Y=y) = \frac {4!}{x!y!(4-x-y)!}\left(\frac 1 3\right)^x\left(\frac 1 2\right)^y
\left(1-\frac 1 3 -\frac 1 2\right)^{(4-x-y)}$$

[Edit]: I see Ray beat me to it by a full minute. :smile:
 
Last edited:
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  • #4
Thanks! That does make the calculations easier and helps me on another similar problem.
 

Related to Better way to do this probability problem?

1. What is the difference between theoretical and experimental probability?

Theoretical probability is based on mathematical calculations and assumptions, while experimental probability is based on actual data collected through experiments or observations.

2. How can I determine the probability of dependent events?

To determine the probability of dependent events, you need to multiply the probability of the first event by the probability of the second event, given that the first event has already occurred.

3. Can you explain the concept of conditional probability?

Conditional probability is the probability of an event occurring given that another event has already occurred. It is calculated by dividing the probability of the two events occurring together by the probability of the first event occurring.

4. What is the difference between permutation and combination?

Permutation is the arrangement of a set of objects where order matters, while combination is the selection of a subset of objects where order does not matter.

5. How do I calculate the probability of a compound event?

To calculate the probability of a compound event, you need to add the individual probabilities of each event, keeping in mind any overlaps or dependencies between the events.

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