Conditional Probability for discrete random variables.

In summary, the writer does not seem to understand what the 1/3 and 2/3 for 0 and 1 represent. They are just examples and should not be used in the actual calculation.
  • #1
XodoX
203
0

Homework Statement


Compute P(X=k l X+Y=p)

Homework Equations


The Attempt at a Solution



No idea. Kind of understand page #1. Although it seems like there's a lot of unnecessary stuff. Could have gone straight from the top to the bottom. And I don't know why/if you even have to substitute the X+Y=p for Y=k-p. Totally lost on page 2. No idea what's going on there. Says it's being split up because it's independent, but no idea where the 1/3 and 2/3 for 0 and 1 come form. Let alone the rest of page 2. :uhh:
So, in short: What's exactly step 1,2,3 etc. ?
 

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  • #2
XodoX said:

Homework Statement


Compute P(X=k l X+Y=p)


Homework Equations





The Attempt at a Solution



No idea. Kind of understand page #1. Although it seems like there's a lot of unnecessary stuff. Could have gone straight from the top to the bottom. And I don't know why/if you even have to substitute the X+Y=p for Y=k-p. Totally lost on page 2. No idea what's going on there. Says it's being split up because it's independent, but no idea where the 1/3 and 2/3 for 0 and 1 come form. Let alone the rest of page 2. :uhh:
So, in short: What's exactly step 1,2,3 etc. ?

The 1/3 and 2/3 for 0 and 1, etc., are just examples, so the writer has some definite numbers to work with when practicing use of the formulas.

RGV
 
  • #3
I'm also trying to solve this similar problem, and also have no idea how to go about solving it.
 
  • #4
mathmajor23 said:
I'm also trying to solve this similar problem, and also have no idea how to go about solving it.

For two events A and B we have
[tex]P(A|B) = \frac{P(A \cap B)}{P(B)}.[/tex]

That's all there is to it. Just figure out what are the events A and B in your problem.

RGV
 
Last edited:

1. What is conditional probability for discrete random variables?

Conditional probability for discrete random variables is a mathematical concept that calculates the likelihood of an event occurring based on the knowledge of another event. It takes into account the probability of both events happening together.

2. How is conditional probability for discrete random variables calculated?

Conditional probability for discrete random variables is calculated by dividing the joint probability of the two events by the probability of the condition. This can be expressed as P(A|B) = P(A and B) / P(B).

3. Can conditional probability be applied to any type of random variable?

Yes, conditional probability can be applied to any type of random variable, whether it is discrete or continuous. However, the calculations may differ depending on the type of variable.

4. How is conditional probability useful in scientific research?

Conditional probability is useful in scientific research as it allows for the calculation of the likelihood of an event occurring in a specific condition. This can help in making predictions and understanding the relationship between variables.

5. What is the difference between conditional probability and joint probability?

Conditional probability takes into account the probability of an event occurring given the knowledge of another event, while joint probability calculates the probability of both events happening together. In other words, conditional probability is a subset of joint probability.

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