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Statistical inference is the process of drawing conclusions from data that are subject to random variation, for example, observational errors or sampling variation.^{[1]} 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.^{[2]} Initial requirements of such a system of procedures for inference and induction are that the system should produce reasonable answers when applied to welldefined 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.
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