In statistics, statistical inference is the process of drawing conclusions from data that is subject to random variation, for example, observational errors or sampling variation. More substantially, the terms statistical inference, statistical induction and inferential statistics are used to describe systems of procedures that can be used to draw conclusions from datasets arising from systems affected by random variation, such as observational errors, random sampling, or random experimentation. Initial requirements of such a system of procedures for inference and induction are that the system should produce reasonable answers when applied to well-defined situations and that it should be general enough to be applied across a range of situations.
The outcome of statistical inference may be an answer to the question "what should be done next?", where this might be a decision about making further experiments or surveys, or about drawing a conclusion before implementing some organizational or governmental policy.
Read more about Statistical Inference: Models/Assumptions, Modes of Inference, Inference Topics
Famous quotes containing the word inference:
“The inference is, that God has restated the superiority of the West. God always does like that when a thousand white people surround one dark one. Dark people are always “bad” when they do not admit the Divine Plan like that. A certain Javanese man who sticks up for Indonesian Independence is very lowdown by the papers, and suspected of being a Japanese puppet.”
—Zora Neale Hurston (1891–1960)