Essay On Gaussian Distribution

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The Gaussian distribution—a function that tells the probability that any real observation will fall between any two real limits or real numbers, as the curve approaches zero on either side. It is a very commonly occurring continuous probability distribution. In theory, Gaussian distributions are extremely important in statistics and are often used in the natural and social sciences for real-valued random variables whose distributions are not known. Gaussian distributions are also sometimes referred as Bell curve or normal distribution.
The probability density function of a normal (or Gaussian) distribution is defined as

Where the parameters μ is the mean or expectation of the distribution σ is the Standard deviation of the distribution σ 2 is the variance of the distribution.
And is represented as

The normal distribution is very utilizable because of the central limit theorem, which states that, under mild conditions, the mean of many arbitrary variables independently drawn from the same distribution is distributed approximately customarily, irrespective of the form of the pristine distribution: physical quantities that are expected to be the sum of many independent processes (such as quantification errors) often have a distribution very proximate to the Gaussian. Moreover, many results and methods (such as propagation of dubiousness and least squares parameter fitting) can be derived analytically in explicit form when the germane variables are normally distributed.
Normal distribution curves are symmetrical about the mean and the curve has some o special properties like:
1) The mean, median and mode are equal.
2) Graph is symmetrical about the mean.
3) The two ends are asymptotic to horizontal ...

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...ghly mundane distributions, with few members at the high and low ends and many in the middle.
Because they occur so frequently, there is an infelicitous propensity to invoke mundane distributions in situations where they may not be applicable. As Lippmann verbally expressed, "Everybody believes in the exponential law of errors: the experimenters, because they cerebrate it can be proved by mathematics; and the mathematicians, because they believe it has been established by observation"
Among the astounding properties of the mundane distribution are that the mundane sum distribution and mundane difference distribution obtained by respectively integrating and subtracting varieties X and Y from two independent mundane distributions with arbitrary betokens and variances are additionally mundane! The mundane ratio distribution obtained from X/Y has a Cauchy distribution.

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