| Description |
1 online resource (x, 325 pages) |
| 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.-- Provided by Publisher. |
| Bibliography |
Includes bibliographical references and index. |
| Contents |
Statistical vocabulary -- Reasoning with probability -- Probabilities in the long run -- Introducing the logic of inference using confidence intervals -- Bayesian and traditional hypothesis testing -- Comparing groups and analyzing experiments -- Associations between variables -- Linear multiple regression -- Interactions in ANOVA and regression -- Logistic regression -- Analyzing change over time -- Dealing with too many variables -- All together now. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Bayesian statistical decision theory -- Problems, exercises, etc.
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Bayesian statistical decision theory -- Data processing.
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Mathematical statistics -- Problems, exercises, etc.
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Mathematical statistics -- Data processing.
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R (Computer program language)
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Statistics.
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statistics. |
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MATHEMATICS -- Applied. |
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MATHEMATICS -- Probability & Statistics -- General. |
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Statistics |
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Bayesian statistical decision theory |
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Bayesian statistical decision theory -- Data processing |
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Mathematical statistics |
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Mathematical statistics -- Data processing |
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R (Computer program language) |
| Genre/Form |
Problems and exercises
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| Other Form: |
Print version: Stanton, Jeffrey M., 1961- Reasoning with data. New York : The Guilford Press, [2017] 9781462530267 (DLC) 2017004984 (OCoLC)960845674 |
| ISBN |
9781462530298 (electronic bk.) |
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146253029X (electronic bk.) |
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9781462530267 (paperback ; alk. paper) |
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1462530265 (paperback ; alk. paper) |
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9781462530274 (hardcover ; alk. paper) |
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1462530273 (hardcover ; alk. paper) |
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