Ron C. Mittelhammer

Mathematical Statistics for Economics and Business (eBook, PDF)

• Format: PDF

Produktbeschreibung

A comprehensive introduction to the principles underlying statistical analyses in the fields of economics, business, and econometrics. The selection of topics is specifically designed to provide students with a substantial conceptual foundation, from which to achieve a thorough and mature understanding of statistical applications within the fields. After introducing the concepts of probability, random variables, and probability density functions, the author develops the key concepts of mathematical statistics, notably: expectation, sampling, asymptotics, and the main families of distributions. The latter half of the book is then devoted to the theories of estimation and hypothesis testing with associated examples and problems that indicate their wide applicability in economics and business. Includes hundreds of exercises and problems.

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Produktdetails

• Verlag: Springer New York
• Seitenzahl: 724
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9781461239888
• Artikelnr.: 44175623

Autorenporträt

Ron Mittelhammer is a Regents Professor of Economic Sciences and Statistics at Washington State University. He is also a Fellow of the Journal of Econometrics, a Fellow of the Agricultural and Applied Economics Association (AAEA), and a Distinguished Scholar of the Western Ag. Economics Association. He has over 250 publications and presentations to his credit, including 100 refereed journal publications. He is a celebrated teacher at the graduate level, receiving national and university-wide awards for instruction, including the AAEA Award for Distinguished Graduate Teaching, the Washington State University Sahlin Faculty Excellence Award in Teaching, and the WSU-CAHNRS Teaching Excellence Award. He served as President-Elect, President, and Past-President of the AAEA from 2008-2011.

Inhaltsangabe

Elements of Probability Theory.- Random Variables, Densities, and Cumulative Distribution Functions.- Expectations and Moments of Random Variables.- Parametric Families of Density Functions.- Basic Asymptotics.- Sampling, Sample Moments, Sampling Distributions, and Simulation.- Point Estimation Theory.- Point Estimation Methods.- Hypothesis Testing Theory.- Hypothesis Testing Methods and Confidence Regions.- Appendix.