Information om | Engelska ordet T-DISTRIBUTION

Exempel på hur man kan använda T-DISTRIBUTION i en mening

• Gosset published under the pen name Student and developed most famously Student's t-distribution – originally called Student's "z" – and "Student's test of statistical significance".
• It is also a component of the definition of the t-distribution and the F-distribution used in t-tests, analysis of variance, and regression analysis.
• There are also generalizations when the components have unequal variance or correlations (Hoyt distribution), or when the vector Y follows a bivariate Student t-distribution (see also: Hotelling's T-squared distribution).
• Hotelling is known to statisticians because of Hotelling's T-squared distribution which is a generalization of the Student's t-distribution in multivariate setting, and its use in statistical hypothesis testing and confidence regions.
• Lindeberg used line transect methods in forestry, and when in 1926 determining the necessary number of transects to obtain a sufficiently precise confidence interval, he seems to have rediscovered Student's t-distribution.
• The brewery hired the statistician William Sealy Gosset in 1899, who achieved lasting fame under the pseudonym "Student" for techniques developed for Guinness, particularly Student's t-distribution and the even more commonly known Student's t-test.
• by replacing estimators that are optimal under the assumption of a normal distribution with estimators that are optimal for, or at least derived for, other distributions; for example, using the t-distribution with low degrees of freedom (high kurtosis) or with a mixture of two or more distributions.
• The cumulative distribution function of noncentral t-distribution with ν degrees of freedom and noncentrality parameter μ can be expressed as.
• The sample extrema can be used for a simple normality test, specifically of kurtosis: one computes the t-statistic of the sample maximum and minimum (subtracts sample mean and divides by the sample standard deviation), and if they are unusually large for the sample size (as per the three sigma rule and table therein, or more precisely a Student's t-distribution), then the kurtosis of the sample distribution deviates significantly from that of the normal distribution.
• The two are in fact equivalent except for parameterization; hence, the Student's t-distribution can still be used for either predictive distribution, but the hyperparameters must be reparameterized before being plugged in.

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