Željko Ivezi,Andrew J. Connolly,Jacob T. VanderPlas,Alexander Gray,Željko Ivezi,Andrew J. Connolly,Jacob T. VanderPlas,Alexander Gray
出处
期刊:Princeton University Press eBooks [Princeton University Press] 日期:2014-01-12
标识
DOI:10.23943/princeton/9780691151687.003.0004
摘要
This chapter introduces the main concepts of statistical inference, or drawing conclusions from data. There are three main types of inference: point estimation, confidence estimation, and hypothesis testing. There are two major statistical paradigms which address the statistical inference questions: the classical, or frequentist paradigm, and the Bayesian paradigm. While most of statistics and machine learning is based on the classical paradigm, Bayesian techniques are being embraced by the statistical and scientific communities at an ever-increasing pace. The chapter begins with a short comparison of classical and Bayesian paradigms, and then discusses the three main types of statistical inference from the classical point of view.