2002•Teaching StatisticsRequires access

Statistical inference

Andrew Gelman, Deborah Nolan

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Abstract

Abstract We begin this chapter with a very successful demonstration illustrating many of the general principles of statistical inference, including estimation, bias, and the concept of the sampling distribution. We then present various demonstrations and examples that take the students on the transition from probability to hypothesis testing, confidence intervals, and more advanced concepts such as statistical power and multiple comparisons.

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What this paper is about

Abstract We begin this chapter with a very successful demonstration illustrating many of the general principles of statistical inference, including estimation, bias, and the concept of the sampling distribution. We then present various demonstrations and examples that take the students on the transition from probability to hypothesis testing, confidence intervals, and more advanced concepts such as statistical power and multiple comparisons.

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Available abstract

Abstract We begin this chapter with a very successful demonstration illustrating many of the general principles of statistical inference, including estimation, bias, and the concept of the sampling distribution. We then present various demonstrations and examples that take the students on the transition from probability to hypothesis testing, confidence intervals, and more advanced concepts such as statistical power and multiple comparisons.

Key concepts: Statistical inference, Fiducial inference, Sampling distribution, Inference, Computer science, Statistical hypothesis testing, Statistical theory, Statistical power

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