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Nevermind sorry, think I've found a sufficent article on wikipedia to help me:
http://en.wikipedia.org/wiki/Gaussian_integral
http://en.wikipedia.org/wiki/Gaussian_integral
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Gib Z said:From memory the Gaussian integral is from infinity to negative infinity..if you want something that act's as an anti derivative, try the Error Function ( erf(x) )
EDIT: ~sigh~ I just realized the erf(x) also has bounds, my bad.
The Gaussian Integral, also known as the Normal Integral or the Error Function, is a mathematical function that describes the area under the bell-shaped curve known as the Gaussian distribution. It is used in many fields of science, including statistics, physics, and engineering.
The Gaussian Integral is calculated using the following formula: ∫-∞∞ e-x2 dx. This integral cannot be solved using basic algebraic methods, but can be evaluated numerically or approximated using various techniques, such as the trapezoidal rule or Simpson's rule.
The Gaussian Integral is significant because it allows for the calculation of probabilities and areas under the Gaussian curve, which is commonly seen in natural phenomena and data sets. It is also used in many mathematical and statistical models, making it a crucial tool in various scientific fields.
The Gaussian Integral has numerous applications in science and technology. It is used in physics to describe the probability distribution of particles, in engineering to model noise and signal processing, and in statistics to analyze data and make predictions. It is also used in financial modeling, image processing, and many other areas.
While the Gaussian Integral is a powerful tool, it does have some limitations. It assumes that the data follows a normal distribution, which may not always be the case. It also cannot be evaluated using simple algebraic methods, so numerical or approximative techniques must be used. Additionally, it may not provide accurate results for extreme values or outliers in a data set.