In most larger samplings of data, some data points will be further away from the sample mean than what is deemed reasonable. This can be due to incidental systematic error or flaws in the theory that generated an assumed family of probability distributions, or it may be that some observations are far from the centre of the data. Outlier points can therefore indicate faulty data, erroneous procedures, or areas where a certain theory might not be valid. However, in large samples, a small number of outliers is to be expected (and not due to any anomalous condition).
Katika sampuli kubwa zaidi za data, baadhi ya pointi za data zitakuwa mbali zaidi na wastani wa sampuli kuliko inavyoonekana kuwa sawa. Hii inaweza kuwa kwa sababu ya hitilafu ya kimfumo au dosari katika nadharia iliyozalisha familia inayodhaniwa ya usambazaji wa uwezekano, au inaweza kuwa kwamba uchunguzi fulani uko mbali na kitovu cha data. Kwa hivyo vidokezo vya nje vinaweza kuonyesha data mbovu, taratibu zenye makosa, au maeneo ambayo nadharia fulani inaweza kuwa si sahihi. Walakini, katika sampuli kubwa, idadi ndogo ya wauzaji inapaswa kutarajiwa (na sio kwa sababu ya hali yoyote isiyo ya kawaida).