Statistical inference is the process of using thedata analysis to infer properties of an underlying probability distribution. Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is sampled from a larger population.
Inferential statistics can be compared to descriptive statistics. Descriptive statistics are concerned only with the properties of the observed data and do not rely on the assumption that the data comes from a larger population.
In machine learning, the term inference is sometimes used instead to mean "to make a prediction, by evaluating an already trained model" In this context, the deduction of model properties is called training or learning (rather than inference ), and the use of a model because the prediction is called inference (instead of prediction); see also predictive inference.
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