Editing Point estimation (section)

=== Sufficiency ===
In statistics, the job of a statistician is to interpret the data that they have collected and to draw statistically valid conclusion about the population under investigation. But in many cases the raw data, which are too numerous and too costly to store, are not suitable for this purpose. Therefore, the statistician would like to condense the data by computing some statistics and to base their analysis on these statistics so that there is no loss of relevant information in doing so, that is the statistician would like to choose those statistics which exhaust all information about the parameter, which is contained in the sample. We define [[sufficient statistic]]s as follows: Let X =( X<sub>1</sub>, X<sub>2</sub>, ... ,X<sub>n</sub>) be a random sample. A statistic T(X) is said to be sufficient for θ (or for the family of distribution) if the conditional distribution of X given T is free from θ.<ref name=":1">{{Cite book|title=Estimation and Inferential Statistics|publisher=Pradip Kumar Sahu, Santi Ranjan Pal, Ajit Kumar Das|year=2015|language=English}}</ref>