Calculating Joint Probability - Get the Answer!

In summary, the conversation discusses the observation that the probabilities of certain events occurring are the same, regardless of the specific index used. This is shown through the equations \(P(X_j=1,X_k=1)=P(X_1=1,X_2=1)\) and \(P(X_1=1,X_2=1)=P(X_1=1)+P(X_2=1|X_1=1)\). The informal explanation is that the probabilities are all the same due to the arbitrary labeling of indices. This is further supported by the fact that \(P(X_2=1|X_1=1)=P(X_2=1|X_5=1)\) and \(P
  • #1
Usagi
45
0
http://img151.imageshack.us/img151/6002/variance.jpg

Just wondering, how did they get the part boxed in blue?

Thanks.
 
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  • #2
Usagi said:
http://img151.imageshack.us/img151/6002/variance.jpg

Just wondering, how did they get the part boxed in blue?

Thanks.
The part in the box comes from the observation that:

\[P(X_j=1,X_k=1)=P(X_1=1,X_2=1), \ \ j\ne k\],

and that:

\[P(X_1=1,X_2=1)=P(X_1=1)+P(X_2=1|X_1=1)\]

CB
 
  • #3
Thanks for that, I realized it too however how does one show that $P(X_j, X_i) = P(X_1, X_2) = P(X_1, X_5)$ and so on?

It isn't so obvious to me that $P(X_1, X_2) = P(X_1, X_5)$
 
  • #4
Usagi said:
Thanks for that, I realized it too however how does one show that $P(X_j, X_i) = P(X_1, X_2) = P(X_1, X_5)$ and so on?

It isn't so obvious to me that $P(X_1, X_2) = P(X_1, X_5)$

The informal explanation is that as the labelling is essentialy arbitary the probabilities are all the same.

More formally:

\[P(X_1=1,X_2=1)=P(X_2=1)+P(X_2)P(X_1=1|P(X_2=1)\]

But \(P(X_2=1|X_1=1)=P(X_2=1|X_5=1)\) and \(P(X_2=1)=P(X_5=1)\). which look better but is still just an observation that the idexing is arbitary and you can just permute indices.

CB
 
  • #5
Thanks :)
 

Related to Calculating Joint Probability - Get the Answer!

1. What is joint probability?

Joint probability is a statistical measure that calculates the likelihood of two or more events occurring together. It is the probability of the intersection of two or more events.

2. How do you calculate joint probability?

To calculate joint probability, you need to multiply the individual probabilities of each event. For example, if event A has a probability of 0.5 and event B has a probability of 0.3, the joint probability of A and B occurring together is 0.5 x 0.3 = 0.15.

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

Joint probability calculates the likelihood of two or more events occurring together, while conditional probability calculates the likelihood of one event occurring given that another event has already occurred.

4. How is joint probability used in real life?

Joint probability is used in various fields such as finance, medicine, and engineering to analyze and predict the likelihood of multiple events occurring together. For example, in finance, joint probability can be used to calculate the probability of a stock portfolio's performance based on the performance of individual stocks.

5. Can joint probability be greater than 1?

No, joint probability cannot be greater than 1. This is because the probability of an event occurring cannot be greater than the total number of possible outcomes. Therefore, the maximum value of joint probability is 1, and it represents a 100% chance of the events occurring together.

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