Statistical inference

branch of applied probability theory

process of deducing properties of an underlying probability distribution by analysis of data

thumb|300px|Figure 1.  The green line represents an overfitted model and the black line represents a regularized model. While the green line best follows the training data, it is too dependent on that data and is likely to have a higher error rate on new unseen data, illustrated by black-outlined dots, compared to the black line. thumb|300x300px|Figure 2.  Noisy (roughly linear) data is fitted to a linear function and a polynomial function. Although the polynomial function is a perfect fit, the linear function can be expected to generalize better: If the two functions were used to ex

branch of statistics that is not based solely on parametrized families of probability distributions

branch of statistics which assumes that sample data come from a population that can be adequately modeled by a probability distribution that has a fixed set of parameters

probability distribution of a sample statistic

family of statistical methods based on sampling of available data

statistical inference based on frequency and proportion in sample data

model for decision analysis