A test for normality in the presence of outliers - Pooi, Ah Hin *; Soo, Huei Ching * (2012)
The Jarque-Bera test is a test based on the coefficients of skewness (S) and kurtoss (K) for testing whether the given random sample is from a normal population. When the random sample of size n constains m outliers, we use the remaining n -- m observations to compute two statistics S* and K* which mimics the statistics S and K. The statistics S* and K* are next transformed to z1 and Z2 which are uncorrelated and having standard normal distributions when the original population is normal. We show that the acceptance region given by a circle in the z1 -- z2 plane is suitable for testing the normality assumption.