摘要: Abstract This chapter reviews some basic concepts in statistical inference and prediction. Sufficiency the likelihood principle are backbones of parametric inference. Method moments maximum among most popular methods point estimation. Finite sample properties estimators assessed using bias, variance, or mean squared error, while asymptotic pertain to behavior when size approaches infinity. Confidence intervals their relationship hypothesis testing described. Additional topics include Bayesian statistics, prediction, model selection.
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