Abstract
In this chapter we review some terminology and basic concepts in probability and classical statistical inference which provide the notation and fundamental background to be used throughout this book. In the section on probability we describe some basic notions and list some common distributions along with their mean, variance, skewness, and kurtosis. We also describe various modes of convergence and end with central limit theorems. In the section on statistical inference, we begin with the subjects of estimation and hypothesis testing and proceed with the notions of contiguity and composite likelihood.
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Alvo, M., Yu, P.L.H. (2018). Fundamental Concepts in Parametric Inference. In: A Parametric Approach to Nonparametric Statistics. Springer Series in the Data Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-94153-0_2
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DOI: https://doi.org/10.1007/978-3-319-94153-0_2
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