Gaussian Function in Statistics

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SUMMARY

The discussion centers on the Gaussian function, specifically its application in calculating the area under the standard normal distribution. The Gaussian function is defined as f(x)=\frac{1}{\sqrt{2 \pi \sigma^{2}}}e^{\frac{(x-\mu)^{2}}{2 \sigma^{2}}}, where μ represents the mean and σ the standard deviation. It is established that there is no finite formula for the antiderivative of the Gaussian function using only elementary functions, necessitating the use of numerical methods for integration. Tools like Wolfram Alpha are commonly employed to assist in these calculations.

PREREQUISITES
  • Understanding of the Gaussian function and its parameters (mean and variance).
  • Familiarity with the fundamental theorem of calculus.
  • Basic knowledge of numerical integration techniques.
  • Experience with statistical concepts related to normal distribution.
NEXT STEPS
  • Explore numerical integration methods for approximating the area under curves.
  • Learn about the properties and applications of the Gaussian Integral.
  • Study the derivation and implications of the standard normal distribution.
  • Investigate advanced mathematical software tools like Wolfram Alpha for statistical analysis.
USEFUL FOR

Students in statistics, mathematicians, and data analysts who require a deeper understanding of the Gaussian function and its applications in probability and statistics.

QuarkCharmer
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Homework Statement


Not really a homework problem, but something that I was curious about. I was thinking about how a calculator finds the area under the standard normal distribution, and I started to assume that it most likely has the antiderivative for the function that makes the standard normal curve, and it simply substitutes the various z-score values for the F(b)-F(a) part of the fundamental theorem of calculus.

Homework Equations


The Gaussian Function:
f(x)=\frac{1}{\sqrt{2 \pi \sigma^{2}}}e^{\frac{(x-\mu)^{2}}{2 \sigma^{2}}}

The Attempt at a Solution


I know at my current math level, I have no hope of integrating this function, (thankfully wolfram and others can aid me), but I was wondering what they use for the mean(mu) and the variance(sigma), and how they came up with that? I think it would be handy to know this.

Alternatively, is the calculator using the Gaussian Integral to perform this task instead?
f(x)=e^{-x^{2}}
 
Last edited:
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It is a rigorously-proven *theorem* that there is NO finite formula for the antiderivative of the Gaussian that involve only elementary functions (trig functions, exponentials, powers and inverses of all these). There are various infinite series, etc., but these are not "finite". Typically, numerical methods would involve approximate formulas of varying complexity and precision. The best of these might achieve full machine accuracy, but if expanded out to many more decimal places would start to reveal discrepancies between exact values (computed, say, using numerical integration) and the results from the formula.

RGV
 
Last edited:

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