Method of Indicators for computing expectation

In summary: The indicator method seems to be the most efficient way to solve this problem.In summary, The conversation discusses a problem involving flipping a coin with a chance p of landing heads, and determining the expected value and variance of the number of head runs in n flips. The indicator method is suggested as a possible solution, and it is shown that the expected value can be calculated using a simple formula. The conversation ends with the conclusion that the indicator method may be the most efficient approach to solving the problem.
  • #1
houston07
1
0
Hi,

I have the following problem: Suppose you have a coin that has chance p of landing heads. Suppose you flip the coin n times and let X denote the number of 'head runs' in n flips. A 'head run' is defined as any sequence of heads. For example the sequence HHTHHHHHTTTTHHTHT contains 4 head runs. Given this information, compute E[X] and Var[X].

I cannot understand how to set up the indicator method that will allow me to solve this problem quickly.
 
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  • #2
houston07 said:
Hi,

I have the following problem: Suppose you have a coin that has chance p of landing heads. Suppose you flip the coin n times and let X denote the number of 'head runs' in n flips. A 'head run' is defined as any sequence of heads. For example the sequence HHTHHHHHTTTTHHTHT contains 4 head runs. Given this information, compute E[X] and Var[X].

I cannot understand how to set up the indicator method that will allow me to solve this problem quickly.
Define [tex]X_i = 1[/tex] if flip i is the start of a run of heads,
[tex]= 0[/tex] otherwise.

To find E[X] you will need to compute [tex]E[\sum X_i][/tex].

To find Var[X] you will need to compute, in addition, [tex]E[\sum X_i X_j][/tex], where the sum runs over all pairs i, j with i < j.
 
  • #3
Seems interesting, but hard problem. I suspect that the indicator method does not work in case of p [tex]\neq[/tex] 1/2. It is easier to consider a fair coin with p=1/2 at the beginning.
 
  • #4
After a messy, lengthy calculations (not the indicator method) an unexpectedly simple formula for the E(x) occurred:

E(x)=p*(p+n*q) ; q=1-p

I was shocked! Indeed, there must be a simple probabilistic approach that replaces involved calculations and hard analysis. Maybe really the indicator method. Still needs to think about this problem.
 
  • #5
Eero said:
After a messy, lengthy calculations (not the indicator method) an unexpectedly simple formula for the E(x) occurred:

E(x)=p*(p+n*q) ; q=1-p

I was shocked! Indeed, there must be a simple probabilistic approach that replaces involved calculations and hard analysis. Maybe really the indicator method. Still needs to think about this problem.

E(X1)=p and E(Xi)=pq for i>1 so E(X) = p+(n-1)pq = p^2 + npq
 
  • #6
Nice one bpet!

I would not come into this as soon. Do you have a clue how to determine E(Xi*Xj) now, to calculate Var(X)?
 
  • #7
Eero said:
Nice one bpet!

I would not come into this as soon. Do you have a clue how to determine E(Xi*Xj) now, to calculate Var(X)?

Thanks! Similar way, more cases to consider e.g. j=i, j=i+1, j>i+1.
 

FAQ: Method of Indicators for computing expectation

What is the Method of Indicators for computing expectation?

The Method of Indicators is a statistical technique used to estimate the expected value of a random variable. It is based on the Law of Large Numbers, which states that as the number of observations increases, the sample mean will converge to the true population mean.

How does the Method of Indicators work?

The Method of Indicators works by assigning a binary value (0 or 1) to each observation in a sample, depending on whether a certain condition is met or not. The expected value is then calculated by taking the average of these binary values, which represents the probability of the condition being met.

What is the advantage of using the Method of Indicators?

One of the main advantages of the Method of Indicators is its simplicity. It can be applied to a wide range of problems and does not require complex mathematical calculations. It also allows for the estimation of expected values without knowing the underlying probability distribution of the random variable.

What are some common applications of the Method of Indicators?

The Method of Indicators is commonly used in finance, economics, and other fields to estimate expected values of various outcomes. It is also used in decision-making processes to evaluate the potential risks and rewards of different options.

What are the limitations of the Method of Indicators?

While the Method of Indicators is a useful and versatile tool, it has some limitations. It assumes that the observations are independent and identically distributed, which may not always be true in real-world situations. It also requires a large sample size to accurately estimate the expected value.

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