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.
"synopsis" may belong to another edition of this title.
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.
"About this title" may belong to another edition of this title.
£ 10.73 shipping from U.S.A. to United Kingdom
Destination, rates & speedsSeller: Books From California, Simi Valley, CA, U.S.A.
paperback. Condition: Very Good. Seller Inventory # mon0003793372
Quantity: 1 available
Seller: ThriftBooks-Atlanta, AUSTELL, GA, U.S.A.
Paperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 1.3. Seller Inventory # G1462530265I3N00
Quantity: 1 available
Seller: Books From California, Simi Valley, CA, U.S.A.
paperback. Condition: Fine. Seller Inventory # mon0003792585
Quantity: 4 available
Seller: SecondSale, Montgomery, IL, U.S.A.
Condition: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. Seller Inventory # 00087858401
Quantity: 1 available
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New. Seller Inventory # 28748938-n
Quantity: Over 20 available
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # FT-9781462530267
Quantity: 15 available
Seller: CitiRetail, Stevenage, United Kingdom
Paperback. Condition: 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. Seller Inventory # 9781462530267
Quantity: 1 available
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition. Seller Inventory # 28748938
Quantity: Over 20 available
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. pp. 325. Seller Inventory # 370283696
Quantity: 3 available
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. 643. Seller Inventory # B9781462530267
Quantity: 1 available