Reasoning with data : an introduction to traditional and Bayesian statistics using R /
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 class...
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Main Authors: | |
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Published: |
The Guilford Press,
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Publisher Address: | New York, NY : |
Publication Dates: | [2017] |
Literature type: | Book |
Language: | English |
Subjects: | |
Summary: |
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, supplemental reading lists, and links to online videos, interactive materials, and other resources.-- |
Carrier Form: | x, 325 pages : illustrations ; 26 cm |
Bibliography: | Includes bibliographical references (pages 313-315) and index. |
ISBN: |
9781462530267 1462530265 9781462530274 1462530273 |
Index Number: | QA279 |
CLC: | O212.8 |
Call Number: | O212.8/S792 |