[PROBABILITY] Joint probability function for two DISCRETE variables

In summary, the joint probability function of U and V when U = min{X1, X2} and V = X1 + X2 is equal to the probability that X1 + u = v multiplied by the probability that min{X1, X2} = u, which is equal to 1/6 multiplied by the probability that min{X1, X2} = u. To find the cumulative probability function of U, we can use the formula 1-P(X1 > u)*P(X2 > u), but it is unclear how to find the probability function from there.
  • #1
libelec
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0

Homework Statement



X1 and X2 represent the values of two honest dice throws (independent of each other). Find the joint probability function of U and V when:

a) U = min{X1,X2}, V = X1 + X2

The Attempt at a Solution



This is what I thought:

[tex]P(U = u,V = v) = P(\min \left\{ {{X_1},{X_2}} \right\} = u,{X_1} + {X_2} = v) = P({X_1} + {X_2} = v|\min \left\{ {{X_1},{X_2}} \right\} = u)*P(\min \left\{ {{X_1},{X_2}} \right\} = u)[/tex]

[tex]P(U = u,V = v) = P({X_1} + u = v)*P(\min \left\{ {{X_1},{X_2}} \right\} = u) = P({X_1} = v - u)*P(\min \left\{ {{X_1},{X_2}} \right\} = u) = \frac{1}{6}*P(\min \left\{ {{X_1},{X_2}} \right\} = u)[/tex]

Now, my question is, how do I find the probability function of U?

I can work it out to find the cumulative probability function:

[tex]P(U \le u) = P(\min \left\{ {{X_1},{X_2}} \right\} \le u) = 1 - P(\min \left\{ {{X_1},{X_2}} \right\} > u) = 1 - P({X_1} > u,{X_2} > u) = 1 - P({X_1} > u)*P({X_2} > u)[/tex]

[tex]P(U \le u) = 1 - \sum\limits_{{X_1} > u} {\sum\limits_{{X_2} > u} {{p_{{X_1},{X_2}}}} ({X_1},{X_2}) = 1} - \sum\limits_{{X_1} > u} {\sum\limits_{{X_2} > u} {\frac{1}{{36}}} = 1} - \frac{1}{{36}}{\left( {6 - u} \right)^2}[/tex]

But I don't know how to get the probability function from there (if I can).

Any ideas, please?

Thanks.
 
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  • #2
Anybody?
 

1. What is a joint probability function for two discrete variables?

A joint probability function for two discrete variables is a mathematical expression that describes the likelihood of two events occurring simultaneously. It takes into account the probabilities of each individual event and their relationship to each other.

2. How is a joint probability function different from a marginal probability function?

A joint probability function considers the probabilities of two events occurring together, while a marginal probability function only considers the probability of one event occurring on its own. A joint probability function is a two-dimensional function, while a marginal probability function is a one-dimensional function.

3. What is the range of values for a joint probability function?

The range of values for a joint probability function is between 0 and 1, inclusive. A value of 0 indicates that the events are independent and have no relationship to each other, while a value of 1 indicates that the events are not independent and have a perfect relationship.

4. How can a joint probability function be used in real-world applications?

A joint probability function can be used to calculate the likelihood of multiple events occurring together, which can be useful in fields such as statistics, economics, and risk analysis. It can also be used to determine the probability of a specific outcome given certain conditions or variables.

5. Can a joint probability function be extended to more than two discrete variables?

Yes, a joint probability function can be extended to any number of discrete variables. This is known as a multivariate probability distribution, and it considers the probabilities of multiple events occurring simultaneously. The principles and calculations are similar to those used in a joint probability function for two variables.

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