## Normal Distribution

In probability theory, the **normal** (or **Gaussian**) **distribution** is a continuous probability distribution, defined on the entire real line, that has a bell-shaped probability density function, known as the **Gaussian function** or informally as the **bell curve**:

Read more about Normal Distribution.

### Some articles on normal distribution:

**Normal Distribution**- See Also

...

**Normal distribution**Generalized

**normal distribution**Log-

**normal distribution**Skewness ...

**Normal Distribution**- History - Naming

... Since its introduction, the

**normal distribution**has been known by many different names the law of error, the law of facility of errors, Laplace's second law, Gaussian law, etc ... Gauss himself apparently coined the term with reference to the "

**normal**equations" involved in its applications, with

**normal**having its technical meaning of ... However, by the end of the 19th century some authors had started using the name

**normal distribution**, where the word "

**normal**" was used as an adjective – the term ...

... We assume now that the

**distribution**is a fixed

**distribution**in what follows we shall in particular consider the case where is the standard

**normal distribution**, which serves as a classical example of the ... numbers, and which 'characterizes' the

**distribution**in the sense that the following equivalence holds We call such an operator the Stein operator ... For the standard

**normal distribution**, Stein's lemma exactly yields such an operator thus we can take We note that there are in general infinitely many such operators and it still remains an ...

**Normal Distribution**

... In probability theory and statistics, the skew

**normal distribution**is a continuous probability

**distribution**that generalises the

**normal distribution**to allow for non-zero skewness ...

**Normal Distribution**- Version 1 - Applications

... This version of the generalized

**normal distribution**has been used in modeling when the concentration of values around the mean and the tail behavior are of particular interest ... Other families of

**distributions**can be used if the focus is on other deviations from normality ... If the symmetry of the

**distribution**is the main interest, the skew

**normal**family or version 2 of the generalized

**normal**family discussed below can be used ...

### Famous quotes containing the words distribution and/or normal:

“The man who pretends that the *distribution* of income in this country reflects the *distribution* of ability or character is an ignoramus. The man who says that it could by any possible political device be made to do so is an unpractical visionary. But the man who says that it ought to do so is something worse than an ignoramous and more disastrous than a visionary: he is, in the profoundest Scriptural sense of the word, a fool.”

—George Bernard Shaw (1856–1950)

“Our *normal* waking consciousness, rational consciousness as we call it, is but one special type of consciousness, whilst all about it, parted from it by the filmiest of screens, there lie potential forms of consciousness entirely different.”

—William James (1842–1910)