One method for identifying these involves dividing gap by range and is known as Dixon's Q test.
One method for identifying these involves dividing gap by range and is known as Dixon's Q test. Chauvenet's  [shao-veh-nay'z] criterion identifies these when a probability times the sample size is less than one-half, while the critical value of a t-distribution is used to look for these using Grubbs' test. Other methods work by adding or subtracting a multiple of the interquartile range to one of the quartiles. Statistical measures that can be used effectively without eliminating these are called robust, and these are sometimes defined as any measurement more than 3  standard deviations away from the mean. Name these data points that do not fit in with the rest of the data because they are abnormally high or low.
One method for identifying these involves dividing gap by range and is known as Dixon's Q test.
{outliers} [accept outlying points or similar answers]