Gamma Distribution (Statistics)

In summary, the conversation is discussing the probability that a random variable X, which is gamma distributed with a=3 and b=2 (alpha/beta), falls between 1 and 2. The conversation includes an attempt to solve the problem using the gamma distribution formula and an integral, but the final answer does not match the answer in the book. Upon further clarification, it is determined that the notation for alpha and beta in the book is opposite to the notation used in the conversation.
  • #1
kuahji
394
2
A random variable X is gamma distributed with a=3, b=2 (alpha/beta). Determine the probability that 1[tex]\leq[/tex]X[tex]\leq[/tex]2

The first thing I did was plug a & b into the gamma distribution formula 1/(b^a [tex]\Gamma[/tex]a * x^(a-1) * e^(-x/b)

Which I ended up with

1/16(x^2 * e^(-x/2)

Which I then though I'd take the integral from 1 to 2

[tex]\int[/tex] 1/16(x^2 * e^(-x/2) dx = 1/16(-2x^2 * e^-.5 - 8x * e^-.5 - 16e^-.5) & then I evaluated that from 1 to 2. Which gave .06...

The answer in the book gives (b-a)^4/80

So where am I going wrong & am I just approaching this problem in totally the wrong way?
 
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  • #2
Try this for Gamma density.

[tex]f(x)= \frac {\beta^\alpha}{\Gamma(\alpha)}x^{\alpha -1} e^{-\beta x}[/tex]

The books answer would be negative ?
 
Last edited:
  • #3
The book answer wouldn't be negative, it'd be ((2-3)^4)/80.
 
  • #4
Also tried the formula, it does not work, it gives a probability over 11, which clearly can't be. The only difference between the formula I posted & yours is you have e^-bx & I had e^(-x/b).
 
  • #5
I am assuming montoyas7940 looked up the gamma pdf on wikipedia (as I did) and I think that parametrization is correct for your application.

I get:

[itex]\int_{1}^{2} 4x^{2}e^{-2x}dx[/itex]

That doesn't evaluate to 1/80.

Try this maybe: P(1<X<2) = P(X<2)+P(X<1)-1
 
  • #6
Oh, I see. I assumed an extra set of parentheses in the books answer. I used the gamma density from "Probability for Risk Management".
 
  • #7
Unless I fat fingered a key on my calculator,

[itex]\int_{1}^{2} 4x^{2}e^{-2x}dx[/itex]

is not .6 either.
 
  • #8
I read the answer book wrong... sorry. :) Its NOT (b-a)^4/80.

The answer was approx. .0659.

Someone asked about the fact Probability for Risk Management gave a different answer today, but I'm not sure what they eventually decided. Using the formula you give I'm still getting 11.14, but I do recall the professor saying Probability for Risk Managements define their alpha as our beta... what I mean is its flip-flopped from what our notation is in the text we use. Anyway, thanks for your time & the help.
 

1. What is a gamma distribution?

A gamma distribution is a continuous probability distribution that is commonly used to model positive, skewed data. It is characterized by two parameters, shape (α) and rate (β), and is often used to model waiting times or the length of time until a certain number of events occur.

2. How is a gamma distribution different from other distributions?

The gamma distribution is unique in that it is the only continuous probability distribution with two positive parameters that produces a skewed distribution. It is also related to other distributions, such as the exponential distribution and chi-squared distribution.

3. What are some real-world applications of the gamma distribution?

The gamma distribution is commonly used in fields such as finance, reliability engineering, and physics. It can be used to model the time until a failure occurs in a mechanical system, the time between customer arrivals in a queue, or the amount of rainfall in a certain period of time.

4. How do you calculate the mean and variance of a gamma distribution?

The mean of a gamma distribution is equal to α/β and the variance is equal to α/β^2. These values can be calculated using the parameters of the distribution or by using a mathematical formula.

5. Can the gamma distribution be used for data with negative values?

No, the gamma distribution is only applicable to positive values. If your data contains negative values, you may need to consider using a different distribution, such as the normal distribution.

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