Librería:
Better World Books, Mishawaka, IN, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Vendedor de AbeBooks desde 3 de agosto de 2006
Used book that is in excellent condition. May show signs of wear or have minor defects. N° de ref. del artículo 40458670-6
Engaging and accessible, this book teaches readers how to use inferential statistical thinking to check their assumptions, assess evidence about their beliefs, and avoid overinterpreting results that may look more promising than they really are. It provides step-by-step guidance for using both classical (frequentist) and Bayesian approaches to inference. Statistical techniques covered side by side from both frequentist and Bayesian approaches include hypothesis testing, replication, analysis of variance, calculation of effect sizes, regression, time series analysis, and more. Students also get a complete introduction to the open-source R programming language and its key packages. Throughout the text, simple commands in R demonstrate essential data analysis skills using real-data examples. The companion website provides annotated R code for the book's examples, in-class exercises, teaching notes, and slide decks.
Pedagogical Features
*Playful, conversational style and gradual approach; suitable for students without strong math backgrounds.
*End-of-chapter exercises based on real data supplied in the free R package.
*Technical explanation and equation/output boxes.
*Appendices on how to install R and work with the sample datasets.
Acerca del autor:
Jeffrey M. Stanton, PhD, is Associate Provost for Academic Affairs and Professor in the School of Information Studies at Syracuse University. Dr. Stanton's interests center on research methods, psychometrics, and statistics, with a particular focus on self-report techniques, such as surveys. He has conducted research on a variety of substantive topics in organizational psychology, including the interactions of people and technology in institutional contexts. He is the author of numerous scholarly articles and several books, including Information Nation: Education and Careers in the Emerging Information Professions and The Visible Employee: Using Workplace Monitoring and Surveillance to Protect Information Assets--Without Compromising Employee Privacy or Trust. Dr. Stanton’s background also includes more than a decade of experience in business, both in established firms and startup companies.
Título: Reasoning with Data : An Introduction to ...
Editorial: Guilford Publications
Año de publicación: 2017
Encuadernación: Encuadernación de tapa blanda
Condición: Very Good
Librería: ThriftBooks-Atlanta, AUSTELL, GA, Estados Unidos de America
Paperback. Condición: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. Nº de ref. del artículo: G1462530265I3N00
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paperback. Condición: Very Good. Nº de ref. del artículo: mon0003793372
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Paperback. Condición: Good. 1st Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes). Nº de ref. del artículo: 002117419U
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Librería: Books From California, Simi Valley, CA, Estados Unidos de America
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Librería: Textbooks_Source, Columbia, MO, Estados Unidos de America
Paperback. Condición: New. 1st Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes). Nº de ref. del artículo: 002117419N
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Condición: New. Nº de ref. del artículo: 28748938-n
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: FT-9781462530267
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Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: new. Paperback. Engaging and accessible, this book teaches readers how to use inferential statistical thinking to check their assumptions, assess evidence about their beliefs, and avoid overinterpreting results that may look more promising than they really are. It provides step-by-step guidance for using both classical (frequentist) and Bayesian approaches to inference. Statistical techniques covered side by side from both frequentist and Bayesian approaches include hypothesis testing, replication, analysis of variance, calculation of effect sizes, regression, time series analysis, and more. Students also get a complete introduction to the open-source R programming language and its key packages. Throughout the text, simple commands in R demonstrate essential data analysis skills using real-data examples. The companion website provides annotated R code for the book's examples, in-class exercises, teaching notes, and slide decks. Pedagogical Features *Playful, conversational style and gradual approach; suitable for students without strong math backgrounds. *End-of-chapter exercises based on real data supplied in the free R package. *Technical explanation and equation/output boxes. *Appendices on how to install R and work with the sample datasets. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9781462530267
Cantidad disponible: 1 disponibles