φ_(μ,σ²)(x)=1/(σ√),e²)/(2σ²))=1/σφ((x-μ)/σ), x∈ℝ.
Source: wiktionary
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φ_(μ,σ²)(x)=1/(σ√),e²)/(2σ²))=1/σφ((x-μ)/σ), x∈ℝ.
Source: wiktionary
It begins with the normal distribution, which is the limiting form of the sample sum over an arbitrary population.
Source: wiktionary
The normal distribution is the backbone of traditional statistics. We learn very early in our statistics training that the distribution of sample means, regardless of the shape of the parent distribution, approaches a normal distribution as the sample size increases.
Source: wiktionary
The development of the general theories of the normal distributions began with the work of de Moivre (1733, 1738) in his studies of approximations to certain binomial distributions for large positive integer n > 0.
Source: wiktionary