How do I evaluate gaussian integrals with positive, real constants?

In summary, the book suggests considering the gaussian distribution with constants A, m, and a, and finding the relevant integrals to evaluate it. The integral of e-x2 is pi1/2, but it is unclear how to relate this to the given equation. The average for x <x> and x2 <x2> can be found by evaluating the integral of xp(x) from infinity to negative infinity, but this method may result in a value of 0 and further clarification is needed.
  • #1
agingstudent
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Homework Statement



The book says to consider the gaussian distribution

p(x) = Ae-m(x-a)2

where A, m, and a are all positive, real constants.

I have no idea how to evaluate this! The book says to look up the relevant integrals. I see the integral of e-x2is pi1/2 but I don't know how to relate that to this equation. My guess is the integral is Api1/2but I think m should appear somewhere in that equation.

I also need to find the average for x <x> and the average of x2<x2> BUT when I try to find this by evaluating the integral of xp(x) from infinity to negative infinity I just get 0, and that doesn't seem correct.



The Attempt at a Solution

 
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  • #2
Try a simple u-substitution, [itex]u=\sqrt{m}(x-a)[/itex]...
 

Related to How do I evaluate gaussian integrals with positive, real constants?

1. What is a gaussian integral?

A gaussian integral is a type of definite integral that involves a function in the form of e-x2. It is commonly used in statistics, physics, and other fields to calculate probabilities and solve problems involving normal distributions.

2. How do you evaluate a gaussian integral?

To evaluate a gaussian integral, you can use various techniques such as completing the square, using substitution, or using the error function. It may also be helpful to use tables or software programs to calculate the value of the integral.

3. What are some applications of gaussian integrals?

Gaussian integrals have many applications in fields such as physics, engineering, and finance. They are used to calculate probabilities, solve differential equations, and analyze data in normal distributions. They are also useful in signal processing and image processing.

4. Can all gaussian integrals be solved analytically?

No, not all gaussian integrals can be solved analytically. Some integrals may have no closed-form solution and require numerical methods to approximate their value. However, many simple gaussian integrals can be evaluated analytically using various techniques.

5. How can I check if I have solved a gaussian integral correctly?

You can check if you have solved a gaussian integral correctly by comparing your answer to known solutions or using integration techniques to verify your result. It is also helpful to check for any potential mistakes or errors in your calculation.

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