How to solve an integral of a gaussian distribution

In summary: The last problem that I have seen that is similar to this (in either calc or prob/stat) is to find the integral of the Gaussian or normal distribution over all real numbers (i.e. find the area under the curve). This is an interesting problem to do either by integration or by using calculus of residues. The result, of course, is that the integral is equal to one.In summary, the conversation discusses the method for solving the integral \int_{-\infty}^\infty\! e ^{(x-a)^{2}}\, dx, which requires a substitution and the use of polar coordinates. It is also mentioned that this integral is commonly used in probability and statistics courses.
  • #1
DragonPetter
830
1

Homework Statement


integrate

[tex]\int_{-\infty}^\infty\! e ^{(x-a)^{2}}\, dx[/tex]

Homework Equations



[tex]\int \! e^u\, du = e^u + C[/tex]

The Attempt at a Solution


i just know that du = 2(x-a), but there is no x to make use of substitution, so I am confused on how to go about solving this since I cannot use substitution
 
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  • #2
EDIT: I'm assuming you mean
[tex]
\int_{-\infty}^\infty\! e ^{-(x-a)^{2}}\, dx
[/tex]​
since what you wrote doesn't converge.Anyway, this is a very tricky integral that requires a trick. By far the best way starts as follows:

First, letting I denote the original integral (after replacing x-a with x), notice that
[tex]I = 2\int_{0}^\infty\! e ^{-x^{2}}\, dx[/tex]​
by symmetry. Next comes the first trick:
[tex]I^2 = 4 \int_{0}^\infty\! e ^{-x^{2}}\, dx \int_{0}^\infty\! e ^{-x^{2}}\, dx = 4 \int_{0}^\infty\! e ^{-x^{2}}\, dx \int_{0}^\infty\! e ^{-y^{2}}\, dy[/tex]​
since the x in the integral is just a dummy variable. But then
[tex]I^2 = 4\int_0^\infty\int_0^\infty\! e ^{-(x^{2}+y^{2})}\,dx\,dy.[/tex]​

The traditional method is to at this point switch to polar coordinates, but a better way (I think) involves the substitution y=xu (so dy=xdu):
[tex]I^2 = 4\int_0^\infty\int_0^\infty\! e^{-x^2(1+u^2)}x\,dx\,du.[/tex]​
From here, I think you should be able to figure this out on your own.
 
  • #3
hmm my textbook is certainly not nice as it leaves this as an exercise with just telling me "(look up any integrals you need)"
and yes, i forgot to include the - sign for the exponential
 
  • #4
DragonPetter said:
hmm my textbook is certainly not nice as it leaves this as an exercise with just telling me "(look up any integrals you need)"

That's wierd.
 
  • #5
On a wild hunch: this seems to be a traditional type problem in a first mathematical stat or calc-based probability course. If you've seen this (normal density integrating to 1)

[tex]
\int_{-\infty}^\infty \frac 1 {\sqrt{2\pi} \sigma} e^{-\frac{(x-\mu)^2}{\sigma^2}} \, dx = 1
[/tex]

the "trick" is to identify your integrand as part of some normal density and go from there.

of course, the item i have posted could be what the hint "look up any integrals needed" refers to as well.
 
  • #6
statdad said:
[tex]
\int_{-\infty}^\infty \frac 1 {\sqrt{2\pi} \sigma} e^{-\frac{(x-\mu)^2}{\sigma^2}} \, dx = 1
[/tex]

You mean
[tex]
\int_{-\infty}^\infty \frac 1 {\sqrt{2\pi} \sigma} e^{-\frac{(x-\mu)^2}{2\sigma^2}} \, dx = 1
[/tex]​
of course
 
  • #7
foxjwill said:
You mean
[tex]
\int_{-\infty}^\infty \frac 1 {\sqrt{2\pi} \sigma} e^{-\frac{(x-\mu)^2}{2\sigma^2}} \, dx = 1
[/tex]​
of course

Yes - many thanks for correcting my typing, and more for possibly clearing up a problem for the original poster.
 

Related to How to solve an integral of a gaussian distribution

What is a gaussian distribution?

A gaussian distribution, also known as a normal distribution, is a probability distribution that is commonly used to model natural phenomena such as heights, weights, and test scores. It is characterized by a bell-shaped curve and is symmetrical around its mean.

What is an integral?

An integral is a mathematical concept that represents the area under a curve. In the context of a gaussian distribution, the integral represents the total probability of a range of values occurring.

Why is solving an integral of a gaussian distribution important?

Solving an integral of a gaussian distribution is important because it allows us to calculate probabilities for a range of values in a normal distribution. This is useful in various fields such as statistics, physics, and economics for making predictions and analyzing data.

What are the steps to solve an integral of a gaussian distribution?

The steps to solve an integral of a gaussian distribution are as follows:

  • 1. Identify the limits of integration, which represent the range of values you want to find the probability for.
  • 2. Use the standard normal distribution table or a calculator to find the corresponding z-scores for the lower and upper limits.
  • 3. Use the formula for the cumulative distribution function (CDF) of a standard normal distribution to calculate the integral.
  • 4. If the limits are not at the mean (0) of the distribution, use the properties of the normal distribution to adjust the CDF formula accordingly.

Can an integral of a gaussian distribution be solved without a calculator?

Yes, an integral of a gaussian distribution can be solved without a calculator using various approximation methods, such as the trapezoidal rule or Simpson's rule. These methods involve dividing the area under the curve into smaller sections and approximating the area of each section with a trapezoid or a parabolic shape, respectively.

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