Finding the Normalization Constant of a Gaussian Distribution (Griffiths 1.6)

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SUMMARY

The normalization constant A for the Gaussian distribution ρ(x) = A e^{-λ(x-a)^{2}} is determined to be A = √(λ/π). This conclusion is reached by evaluating the integral ∫^{∞}_{-∞} ρ(x) dx = 1, which confirms that the area under the Gaussian curve equals one. The discussion highlights the necessity of understanding integrals and the error function (erf) for solving such problems effectively.

PREREQUISITES
  • Understanding of Gaussian distributions
  • Familiarity with integral calculus
  • Knowledge of the error function (erf)
  • Basic concepts of normalization in probability theory
NEXT STEPS
  • Study the derivation of the Gaussian integral
  • Learn about the properties and applications of the error function (erf)
  • Explore change of variables in integrals
  • Investigate other probability distributions and their normalization constants
USEFUL FOR

Students in mathematics or physics, particularly those studying probability theory and statistics, as well as anyone needing to understand Gaussian distributions and their normalization.

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Homework Statement



Consider the Gaussian Distribution

ρ(x) = A e^{-λ(x-a)^{2}}

where A, a, and λ are constants. Determine the normalization constant A.

Homework Equations



\int^{∞}_{-∞}ρ(x) dx = 1

The Attempt at a Solution



The problem recommends you look up all necessary integrals, so I did and I think that I've got it correct. I found that A = \sqrt{\frac{λ}{π}}. My question, if this answer is correct, is just: how do you do this integral? Do you have to actually do some kind of change of variables to a different coordinate system?
 
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TSny said:
See here

Thanks a bunch. I was a little confused because the solution I had found involved erf and I wasn't quite sure how to use it since I'd never seen that function before.
 

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