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Jarque–Bera Test
In statistics, the Jarque–Bera test is a goodness-of-fit test of whether sample data have the skewness and kurtosis matching a normal distribution. The test is named after Carlos Jarque and Anil K. Bera. The test statistic is always nonnegative. If it is far from zero, it signals the data do not have a normal distribution. The test statistic ''JB'' is defined as : \mathit = \frac \left( S^2 + \frac14 (K-3)^2 \right) where ''n'' is the number of observations (or degrees of freedom in general); ''S'' is the sample skewness, ''K'' is the sample kurtosis : : S = \frac = \frac , : K = \frac = \frac , where \hat_3 and \hat_4 are the estimates of third and fourth central moments, respectively, \bar is the sample mean, and \hat^2 is the estimate of the second central moment, the variance. If the data comes from a normal distribution, the ''JB'' statistic asymptotically has a chi-squared distribution with two degrees of freedom, so the statistic can be u ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistics Statistics (from German: '' Statistik'', "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the pla |
