Probability with a recursive definition

In summary, the problem is asking to find the probability of X=0 given that Pr(X=0)=Pr(X=1) and Pr(X=k+1)=(1/k)Pr(X=k) for k=1,2,3,... Using the given information, we can find that P(X=0)=1/e-1, but the correct answer is 1/e+1, indicating an error in the reindexing process.
  • #1
DotKite
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Homework Statement



Suppose that
Pr(X = 0) = Pr(X = 1), Pr(X = k + 1) = (1/k)Pr(X = k), k = 1,2,3,···
Find Pr(0).

Homework Equations





The Attempt at a Solution



Ok I started with k = 1 and went to k = 5. The pattern I noticed is

For k=n we have p(X=n+1) = (1/2)(1/3)(1/4)...(1/n)p(X=1) = (1/n!)p(X=1)

Let k go to inf

We have Ʃ (1/n!) p(X=1)


The above summation equal 1 by probability axiom.

We get p(X=1) = Ʃ 1/n!

It is known that ex = Ʃ xn/n! Where 0≤n<∞

In this case we are starting from 1 so we must reindex to get
ex = 1 + Ʃ xn/n!

We then have

P(X=1) = 1/(Ʃ 1/n!) = 1/e-1

Since p(X=0) = p(X=1) is given we end up with

p(X=0) = 1/e-1

But the answer is 1/e+1. I sense I am close but I am messing up something with the reindexing maybe?
 
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  • #2
DotKite said:

Homework Statement



Suppose that
Pr(X = 0) = Pr(X = 1), Pr(X = k + 1) = (1/k)Pr(X = k), k = 1,2,3,···
Find Pr(0).

Homework Equations





The Attempt at a Solution



Ok I started with k = 1 and went to k = 5. The pattern I noticed is

For k=n we have p(X=n+1) = (1/2)(1/3)(1/4)...(1/n)p(X=1) = (1/n!)p(X=1)

Let k go to inf

We have Ʃ (1/n!) p(X=1)


The above summation equal 1 by probability axiom.

We get p(X=1) = Ʃ 1/n!

It is known that ex = Ʃ xn/n! Where 0≤n<∞

In this case we are starting from 1 so we must reindex to get
ex = 1 + Ʃ xn/n!

We then have

P(X=1) = 1/(Ʃ 1/n!) = 1/e-1

Since p(X=0) = p(X=1) is given we end up with

p(X=0) = 1/e-1

But the answer is 1/e+1. I sense I am close but I am messing up something with the reindexing maybe?

You summed P(X=1)+P(X=2)+P(X=3)+... correctly. It's (Ʃ (1/n!)) p(X=1)=e*P(X=1). Then stuff starts going haywire. The axiom of probability tells you P(X=0)+P(X=1)+P(X=2)+...=1. So P(X=0)+e*p(X=1)=1. Take it from there.
 

1. What is a recursive definition in probability?

A recursive definition in probability is a way of defining a probability function by breaking it down into smaller, simpler components. This allows for a more efficient and organized way of calculating probabilities for complex events.

2. How is a recursive definition used in probability?

In probability, a recursive definition is used to break down a complex event into simpler, more manageable components. This allows for the calculation of probabilities for the entire event by multiplying the probabilities of each component together.

3. Can you provide an example of a recursive definition in probability?

One example of a recursive definition in probability is the calculation of the probability of rolling two dice and getting a sum of 7. This can be broken down into the probability of rolling a 1 on the first die and a 6 on the second die, or a 2 on the first die and a 5 on the second die, and so on. These individual probabilities can then be added together to get the overall probability of rolling a 7.

4. What are the advantages of using a recursive definition in probability?

One advantage of using a recursive definition in probability is that it allows for the efficient calculation of probabilities for complex events. It also provides a clear and organized structure for understanding and solving probability problems.

5. Are there any limitations to using a recursive definition in probability?

One limitation of using a recursive definition in probability is that it may not be applicable to all types of probability problems. In some cases, a different approach may be more suitable. Additionally, if the components in the recursive definition are not independent, the calculated probability may not be accurate.

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