Discrete Bivariate Random Variables

In summary: ZXIgdGhlIHByb2JsZW1zIGZvciB0aGUgYmlydmF0aXZlIGRpc2NvdW50aW5nIG9mIHJvbGxpbmcgdG8gdGVzdCB0aGVyYXB5IGFzIHRoZSB3b3JrIHNpemUgYW5kIG5vdCBtYWRlIHRoZSBwb3NpdGl2ZSBmb3IgKlgyMSkKClRoaXMgZmlyc3QgZm9yIG1lLCBhbmQgaWYgc3
  • #1
adamsmc2
2
0
Here is the question:

Consider the experiment of rolling two tetrahedra that are unfair in the sense that each has the following probabilities for each of the four faces:

P{1 dot}=1/10
P{2 dots}=2/10
P{3 dots}=3/10
P{4 dots}=4/10

Let X be the total of the outcomes in the two tetrahedra and Y be the absolute difference between their outcomes. Obtain the joint probability mass function of (X,Y).

So I am confused on how to do the probabilities since it is unfair and not fair. Help.

Here is the work I've done, I'm stuck and not really sure how to transform this into the joint probability mass function for (X,Y).

photo.jpg


Sorry the photo's sideways, I tried rotating it but it wouldn't translate it into the post.
 
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  • #2
adamsmc2 said:
Here is the question:

Consider the experiment of rolling two tetrahedra that are unfair in the sense that each has the following probabilities for each of the four faces:

P{1 dot}=1/10
P{2 dots}=2/10
P{3 dots}=3/10
P{4 dots}=4/10

Let X be the total of the outcomes in the two tetrahedra and Y be the absolute difference between their outcomes. Obtain the joint probability mass function of (X,Y).

So I am confused on how to do the probabilities since it is unfair and not fair. Help.

Here is the work I've done, I'm stuck and not really sure how to transform this into the joint probability mass function for (X,Y).

photo.jpg


Sorry the photo's sideways, I tried rotating it but it wouldn't translate it into the post.

Are the two tetrahedra independent? If so, and if X1 = value on tet. 1 and X2 = value on tet. 2, then X1 and X2 are independent and have known probability distributions. So, in this case what is the bivariate distribution of the pair (X1,X2)? [Maybe your attached work has already done this, but I can't read it.] Now just get X and Y in terms of X1 and X2.

RGV
 

Related to Discrete Bivariate Random Variables

1. What is a discrete bivariate random variable?

A discrete bivariate random variable is a type of random variable that takes on two values, usually represented by the variables X and Y, with a finite or countably infinite number of outcomes. These outcomes are determined by the joint probability distribution of the two variables.

2. How is a discrete bivariate random variable different from a univariate random variable?

A discrete bivariate random variable differs from a univariate random variable in that it involves two variables instead of just one. This means that the outcomes of the random variable are determined by the joint probability distribution of both variables, rather than just one.

3. What is the joint probability distribution of a discrete bivariate random variable?

The joint probability distribution of a discrete bivariate random variable is a function that assigns probabilities to each possible combination of outcomes for the two variables. It is typically represented by a table or graph, with the probabilities for each combination of outcomes listed or shown.

4. How is the independence of two discrete bivariate random variables determined?

The independence of two discrete bivariate random variables is determined by the joint probability distribution and the individual probability distributions of each variable. If the joint probability distribution can be expressed as the product of the individual probability distributions, then the variables are considered independent.

5. What are some applications of discrete bivariate random variables in science?

Discrete bivariate random variables are commonly used in various fields of science, such as statistics, biology, and engineering. They can be used to model and analyze complex systems with multiple variables, and to make predictions about the behavior of these systems. For example, they may be used to study the effects of two different treatments on a group of patients, or to analyze the performance of a machine with two input variables.

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