What Is the Difference Between Expected Value Calculation Methods?

AI Thread Summary
The discussion clarifies the difference between calculating expected values using probability distributions and binomial distributions. The expected value for a general probability distribution involves summing the products of outcomes and their probabilities, while for binomial distributions, it simplifies to multiplying the number of trials (n) by the probability of success (p). Both methods are fundamentally derived from the same principle, but the binomial approach is more efficient for larger sample sizes. Users are encouraged to derive the binomial expected value formula from the general method to understand the connection better. This understanding is crucial for applying the correct method in different statistical scenarios.
Peter G.
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Hi,

I have to work with Expected Values and I am extremely confused over the following:

In the part of my book that teaches me about Probability Distribution, in order to calculate the Expected Value I have to:

Lets say we toss a coin twice. We can get 0 Heads, 1 Heads or 2 Heads

I then draw a probability distribution table and the expected value is the sum of the product of the number of heads and their respective probabilities.

When I get to the part that I learn about Binomial Distributions, in order to get the expected value all I have to do is multiply n by p whereas n is the number of tries and p the probability of success.

What is the difference between the two methods? When should I use each?

Thanks!
 
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Peter G. said:
Hi,

I have to work with Expected Values and I am extremely confused over the following:

In the part of my book that teaches me about Probability Distribution, in order to calculate the Expected Value I have to:

Lets say we toss a coin twice. We can get 0 Heads, 1 Heads or 2 Heads

I then draw a probability distribution table and the expected value is the sum of the product of the number of heads and their respective probabilities.

When I get to the part that I learn about Binomial Distributions, in order to get the expected value all I have to do is multiply n by p whereas n is the number of tries and p the probability of success.

What is the difference between the two methods? When should I use each?

Thanks!

The equation for the EV of a binomial distribution is derived from the exact same procedure the you have described (sum the product of the outcomes with their respective probabilities) i.e. if X~Bin(n,p), then:

E(X)=\sum_{x=0}^{n}xP(X=x)

So for any n, you could in fact just draw up a table of outcomes and then continue with how you originally solved it, however that will be a lot more work for large n. It is probably a good exercise to try and actually derive the equation E(X)=np from the equation i have posted above, so you can see for yourself that they are identical.

EDIT:
Have a look at this:

http://amath.colorado.edu/courses/4570/2007fall/HandOuts/binexp.pdf

It will show you the derivation. Also keep in mind that this only works for binomial random variables.
 
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