For example, in, matlab, a result of 1 means that the null hypothesis has been rejected at the 5 significance level.
The, where: n is the sample size, b1 is the sample skewness coefficient, b2 is the kurtosis coefficient.
Quality of the table, we think that the approximation table is good enough for practice needs.
Therefore it's better to use the specially created table of Jarque-Bera distribution quantiles.
It is usually used for large data sets, because other normality tests are not reliable when n is large (for example, Shapiro-Wilk isnt reliable with n more than 2,000).For example, a tiny p-value and a large chi-square value from this test means that you can reject the null hypothesis that the data is normally distributed.The null hypothesis is of normality, and rejection of the hypothesis (because of a significant p-value) leads to the conclusion that the distribution from which the data came is non-normal.As a rule, this test is applied before using methods of parametric statistics which require distribution normality.Criterion, this test is based on the fact that skewness and kurtosis of normal distribution equal zero.The author believes that this method allows us to get credible results in a reasonable interval.Jarque-Bera Test was last modified: April 10th, 2017 by Andale.What the Results Mean, in general, a large J-B value indicates that errors are not normally distributed.