Is P(x + a > y + b) Always 0.5 for Independent Variables?

In summary, the conversation discusses a probability proof question involving independent random variables from cumulative distributions F and G. The question is how to show that P(x + a > y + b) = 0.5 without assuming a distribution type. The solution involves using characteristic functions and the fact that the random variable S= x - y + a - b has a symmetric distribution. The conversation also mentions a possible similar question, P(ax < by), but notes that the characteristic function method may not work for this case.
  • #1
Schlotkins
2
0
Good evening:

I have a probability proof question that is driving me crazy. I feel
like I must have forgot an easy trick. Any help is GREATLY
appreciated. Here's the setup:

Let's assume a,b are indepedent random variables from cummulative
distribution F.


I think it's safe to say:


P( a > b) = .5


Now, let's assume x,y are independent random variables from CDF G.
Again:


P(x > y) = 0.5


Assume CDFs G and F are indepedent. Now it seems straightforward that:


P(x + a > y + b) = 0.5


but I don't know how to show it without assuming a distribution type.


Again, any help is appreciated.


Thank you,
Chris
 
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  • #2
If you are familiar with characteristic functions it is simple.
Let f and g be the characteristic functions of F and G.
Then S= x - y + a - b will have a ch. fcn. f(t)f(-t)g(t)g(-t).
This means that S has a symmetric distribution.
 
Last edited:
  • #3
Thank you for the tip and the response - I think I have it solved. On an aside, that trick wouldn't work for P(ax < by) right? It seems obvious that the P(ax - by < 0 ) = P (by - ax < 0)= .5, but of course characteristic functions are most useful for sums.

Thanks again for your assistance.
Chris
 

What is a probability proof question?

A probability proof question is a mathematical problem that requires the use of probability theory to solve. It involves determining the likelihood or chance of a certain event occurring based on given information and assumptions.

What are the key components of a probability proof question?

The key components of a probability proof question include the sample space, which is the set of all possible outcomes, and the event, which is the specific outcome or set of outcomes being considered. The question may also include information about the probability of certain events or the conditions under which the events occur.

How do you approach solving a probability proof question?

The first step in solving a probability proof question is to clearly define the sample space and event being considered. Then, you can use probability rules and formulas, such as the addition rule, multiplication rule, and Bayes' theorem, to calculate the probability of the event. It is also important to carefully consider any given information or assumptions and how they may affect the probability calculation.

What are some common mistakes to avoid when solving a probability proof question?

One common mistake is not properly defining the sample space or event, which can lead to incorrect probability calculations. It is also important to be careful when using probability rules and formulas, as they may not apply in all situations. Another mistake is not considering all given information and assumptions, which can also result in incorrect answers.

How can understanding probability proof questions be useful in real life?

Understanding probability proof questions can be useful in many real-life scenarios, such as making predictions and decisions based on uncertain outcomes. For example, in finance, probability theory is used to assess risk and make investment decisions. In medicine, it is used to evaluate the effectiveness of treatments and diagnose diseases. In everyday life, understanding probability can help with decision-making and understanding the likelihood of certain events occurring.

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