Parameter Estimation

Thomas Cleff ()
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Thomas Cleff: Pforzheim University of Applied Sciences

Chapter Chapter 8 in Applied Statistics and Multivariate Data Analysis for Business and Economics, 2025, pp 243-277 from Springer

Abstract: Abstract This chapter covers parameter estimation, a fundamental aspect of inductive statistics. It allows generalizations to be made about a population based on sample data. The chapter covers two main estimation procedures: point estimation, which provides a single value estimate for population parameters, and interval estimation, which provides an interval within which the parameter is likely to lie. Through illustrative examples and theoretical explanations, the concepts of sampling distributions, standard error, and confidence intervals are explained, emphasizing the importance of sample size and the central limit theorem in ensuring accurate and reliable estimates.

Keywords: Parameter estimation; Point estimation; Interval estimation; Sampling distribution; Standard error; Confidence intervals; Central limit theorem; Sample size; Statistical estimation (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-78070-7_8

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