Marginal PMF values of a function

In summary, the conversation discussed the correctness of the workings for a given question and provided corrections for minor errors. The formula for calculating the probability distribution for x and y was also mentioned.
  • #1
Longines
10
0
Hello once again!

I've been doing this question and I was wondering if my workings are correct, if they are not correct, can you please correct them?

The question is as follows:
View attachment 3243

My workings are:

$\binom{y}{x} \frac{e^{-1}}{2^y y!}$We can rewrite this:

$\frac{y!}{x!(y-x)!} \times \frac{e^{-1}}{2^y y!}$$\frac{1}{x!(y-x)!} \times \frac{e^{-1}}{2^y}$

So we have:
$f_{x, y}(x,y) = \frac{1}{x!(y-x)!} \times \frac{e^{-1}}{2^y}$

Now using the formula:

$f_{x} (x,y) = \sum_{y}^{\infty} P_{x,y}(x,y)$

and subbing in $P_{x,y}(x,y)$:$\frac{e^{-1}}{x!} \sum_{y}^{\infty} \frac{1}{(y-x)!}$

= $\frac{e^{-1}}{x!}$

And in a same fashion, for y we get:

$f_{y}(x,y) = \frac{e^{-1}}{y!}$
 

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  • #2
Hello! Your workings look mostly correct, but there are a few minor errors that I wanted to point out.

Firstly, in the first line where you rewrote the expression, the exponent for 2 should be y-x, not just y. This is because the denominator of the binomial coefficient is (y-x)!, not y!.

Secondly, in the line where you use the formula for f_x(x,y), the summation should start at x, not y. This is because for each value of x, the summation should go from x to infinity, not y to infinity.

Finally, in the last line where you calculate f_y(x,y), the exponent for 2 should be y, not y!. This is because the denominator of the binomial coefficient is y!, not (y-1)!.

Other than these minor errors, your workings look good and you have correctly calculated the probability distributions for x and y. Keep up the good work!
 

FAQ: Marginal PMF values of a function

What are marginal PMF values of a function?

Marginal PMF values of a function refer to the probability mass function of a single variable in a multivariate distribution. It represents the probability of a specific outcome for one variable, while holding all other variables constant.

How are marginal PMF values calculated?

Marginal PMF values can be calculated by summing the joint PMF values for all possible values of the variable of interest. This can be done by marginalizing the joint PMF over all other variables.

What is the significance of marginal PMF values in statistical analysis?

Marginal PMF values are important in statistical analysis because they allow us to examine the relationship between individual variables in a multivariate distribution. They can also provide insights into the overall distribution of a single variable.

How do marginal PMF values differ from marginal PDF values?

Marginal PMF values are discrete probabilities, while marginal PDF values are continuous probabilities. Marginal PMF values are used for discrete random variables, while marginal PDF values are used for continuous random variables.

Can marginal PMF values be used to determine causality?

No, marginal PMF values cannot be used to determine causality. They only show the probability of a specific outcome for a single variable, and cannot account for other variables or factors that may influence the relationship between variables.

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