Perhaps one outlier is enough to create a biased (statistical) pattern when the value is really extreme. These points are often referred to as outliers. In a sense, this definition leaves it up to the analyst (or a consensus process) to decide what will be considered abnormal. Standard Deviation Method What does it mean to be an outlier?Īn outlier is an observation that lies an abnormal distance from other values in a random sample from a population. In the case of normally distributed data, the three sigma rule means that roughly 1 in 22 observations will differ by twice the standard deviation or more from the mean, and 1 in 370 will deviate by three times the standard deviation. The second problem can be solved by applying the normalizing transformations. The second problem is that well-known statistical methods are used to detect outliers in a data set under the assumption that the data is generated by the Gaussian distribution. However, choosing a value of significance level for outlier detection is one of the problems. It is justifiable to exclude ‘outlier’ data points from statistical analysis for significance level of 0.005 or less according R.A. You might notice that some of the reaction times are -9 in the data below. values are numeric values that need to be defined as missing for SPSS. There is a -9 everywhere in the listing that there was a -9 in the data, so the value of the user-defined missing is preserved for the original variables (). The result of the list follows, notice that SPSS marks user-missing values with a -9 in the listing. User-defined missing values on the original variable become system-missing values on the new variables.