Probability Theory - Expectation Problem

In summary, the joint probability mass function for discrete random variables X and Y is given by (x,y) = 2^(-x-y). The marginal probability mass functions for X and Y are pX(x) = 2^-x and pY(y) = 2^-y, respectively. Since pX,Y(x,y) = pX(x) * pY(y), X and Y are independent. The expectations for X and Y can be calculated using the formula E(X) = Σ x*pX(x) and E(Y) = Σ y*pY(y), where x and y are the possible values for X and Y, respectively. In this case, X and Y can take on all positive integer values
  • #1
rooski
61
0

Homework Statement



Discrete random variables X and Y , whose values are positive integers, have the joint probability mass function , (, ) = 2−−. Determine the marginal probability mass functions () and (). Are X and Y independent? Determine [], [ ], and [ ].

The Attempt at a Solution



y=1ʃ∞ pX(x) = Σ pX,Y(x,y)
= y=1ʃ∞ Σ 2^(-x-y)
= y=1ʃ∞ 2^(-x) Σ 2^(-y)
= 2^-x

x=1ʃ∞ pY(y) = Σ pX,Y(x,y)
= x=1ʃ∞ Σ 2^(-x-y)
= x=1ʃ∞ 2^(-y) Σ 2^(-x)
= 2^-y

Since pX,Y(x, y) = pX(x) * pY(y), X and Y are independent of each other.

I am stuck figuring out the expectations. Are we to assume that x and y can only take the values 0 and 1? The expectation requires a weighted average of all the possible values of x and y but the problem does not tell us the possible values...
 
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  • #2
rooski said:

Homework Statement



Discrete random variables X and Y , whose values are positive integers, have the joint probability mass function , (, ) = 2−−. Determine the marginal probability mass functions () and (). Are X and Y independent? Determine [], [ ], and [ ].

The Attempt at a Solution



y=1ʃ∞ pX(x) = Σ pX,Y(x,y)
= y=1ʃ∞ Σ 2^(-x-y)
= y=1ʃ∞ 2^(-x) Σ 2^(-y)
= 2^-x

x=1ʃ∞ pY(y) = Σ pX,Y(x,y)
= x=1ʃ∞ Σ 2^(-x-y)
= x=1ʃ∞ 2^(-y) Σ 2^(-x)
= 2^-y

Since pX,Y(x, y) = pX(x) * pY(y), X and Y are independent of each other.

I am stuck figuring out the expectations. Are we to assume that x and y can only take the values 0 and 1? The expectation requires a weighted average of all the possible values of x and y but the problem does not tell us the possible values...

Yes it does. Your first statement says X and Y take on positive integers.

You have figured out that pX(x) = P(X=x) = 2-x, right? And what is your formula for E(X) for a discrete probability function?
 
  • #3
But if it tells me that it only takes on positive integers then technically it can take on infinite positive integers right? And from what i gather you need to know the range of x in order to calculate the expectations. :S
 
  • #4
rooski said:
But if it tells me that it only takes on positive integers then technically it can take on infinite positive integers right? And from what i gather you need to know the range of x in order to calculate the expectations. :S

The random variable X can take on values 1,2,3,...with various probabilities. You have already figured out P(X = x) = 2-x

In other words
P(X = 1) = 1/2
P(X = 2) = 1/4
P(X = 3) = 1/8
and so on.

So I will ask you again, what is the formula for E(X) when you know its discrete probability function pX(x)?
 

Related to Probability Theory - Expectation Problem

1. What is probability theory and why is it important?

Probability theory is a branch of mathematics that deals with the analysis of random events and their likelihood of occurring. It is important because it allows us to quantify uncertainty and make informed decisions based on the likelihood of different outcomes.

2. What is the expectation problem in probability theory?

The expectation problem refers to the difficulty in accurately predicting the average outcome of a random event. It arises when there is a lack of information or when the event is too complex to be fully understood.

3. How is the expected value calculated in probability theory?

The expected value is calculated by multiplying each possible outcome of a random event by its probability of occurring and then summing all of these values. It represents the average outcome that can be expected over a large number of trials.

4. What is the difference between expected value and actual value?

Expected value is a theoretical concept that represents the average outcome of a random event, while actual value is the observed result of a single trial. The expected value may not always match the actual value, but over a large number of trials, they should be similar.

5. How is probability theory used in real life?

Probability theory is used in many real-life applications, such as predicting stock market trends, weather forecasting, and risk analysis in insurance and finance. It also helps in decision-making processes, such as in game theory and medical diagnosis.

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