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Probability and Statistics for Economics and Business. An Introduction Using R
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- Nombre de pages680
- FormatePub
- ISBN978-0-262-38474-2
- EAN9780262384742
- Date de parution25/11/2025
- Protection num.Adobe DRM
- Taille30 Mo
- Infos supplémentairesepub
- ÉditeurThe MIT Press
Résumé
A modern introduction to probability and statistics for economics and business undergraduates, using the R programming language. Designed for an introductory course in probability and statistics for economics and business undergraduates, this comprehensive textbook introduces students to the R statistical programming language. While covering the standard topics found in traditional textbooks, Jason Abrevaya takes a modern approach that directly integrates R, highlights the use of simulation methods, and provides a general treatment of statistical inference for asymptotically normal estimators.
Coverage emphasizes concepts that are useful to economists and data analysts, including general statistical-inference results that apply well beyond averages and variances. The book offers a higher level of mathematical rigor than traditional business statistics textbooks to prepare students for future coursework and for a professional climate where employers increasingly emphasize competence in data science and statistics.
Introduces students to the R statistical programming language Uses real-world examples and datasets related to economics and business Provides extensive coverage of simulation methods Focuses on large-sample (asymptotic) results Is classroom-tested at Emory University, the University of Texas at Austin, Princeton University, and elsewhere Suits undergraduate and graduate students in business, economics, data science, and statistics with knowledge of calculus Offers companion website and extensive instructor resources
Coverage emphasizes concepts that are useful to economists and data analysts, including general statistical-inference results that apply well beyond averages and variances. The book offers a higher level of mathematical rigor than traditional business statistics textbooks to prepare students for future coursework and for a professional climate where employers increasingly emphasize competence in data science and statistics.
Introduces students to the R statistical programming language Uses real-world examples and datasets related to economics and business Provides extensive coverage of simulation methods Focuses on large-sample (asymptotic) results Is classroom-tested at Emory University, the University of Texas at Austin, Princeton University, and elsewhere Suits undergraduate and graduate students in business, economics, data science, and statistics with knowledge of calculus Offers companion website and extensive instructor resources