Gaussian Function in Statistics

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  • #1
QuarkCharmer
1,051
3

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:
[tex]f(x)=\frac{1}{\sqrt{2 \pi \sigma^{2}}}e^{\frac{(x-\mu)^{2}}{2 \sigma^{2}}}[/tex]

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?
[tex]f(x)=e^{-x^{2}}[/tex]
 
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  • #2
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
 
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Related to Gaussian Function in Statistics

What is Gaussian Function in Statistics?

The Gaussian function, also known as the normal distribution, is a mathematical function that describes the probability distribution of a continuous random variable. It is often used in statistics to model real-world phenomena that are normally distributed.

What is the formula for the Gaussian Function?

The formula for the Gaussian function is:
f(x) = (1/σ√(2π)) * e^(-((x-μ)^2 / 2σ^2))
Where μ is the mean of the distribution and σ is the standard deviation.

What are the characteristics of a Gaussian Function?

The Gaussian function is symmetric, bell-shaped, and unimodal (has only one peak). The mean, median, and mode of a Gaussian distribution are all equal. The area under the curve is equal to 1, and 68% of the data falls within one standard deviation of the mean.

How is the Gaussian Function used in statistics?

The Gaussian function is used to calculate probabilities and make predictions about data that follows a normal distribution. It is also used in hypothesis testing, confidence intervals, and regression analysis.

What is the importance of the Gaussian Function in statistics?

The Gaussian function is one of the most widely used and studied functions in statistics. It allows us to understand and analyze data that follows a normal distribution, which is very common in nature. It also serves as a foundation for many statistical methods and models.

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