This is a unique book. While providing a wealth of examples through lessons and data sets, it is also the best attempt by members of our profession to integrate suggestions from research findings with statistics concepts and pedagogy. What could I do better? The authors have provided a comprehensive overview of the current state-of-the-art in statistics education research. The insights they have gleaned from the literature should be tremendously helpful for those involved i.
Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression.
The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs.
Each chapter has a glossary and comprehension questions. With clever examples and witty takeaways, John Levi Martin proves himself to be a most affable tour guide through these scholarly waters. Martin argues that the task of social statistics isn't to estimate parameters, but to reject false theory. He illustrates common pitfalls that can keep researchers from doing just that using a combination of visualizations, re-analyses, and simulations.
Thinking Through Statistics gives social science practitioners accessible insight into troves of wisdom that would normally have to be earned through arduous trial and error, and it does so with a lighthearted approach that ensures this field guide is anything but stodgy.
Readers quicklymaster and learn to apply statistical methods, such as bootstrap,decision trees, t-test, and permutations to better characterize,report, test, and classify their research findings.
An Excel Primer is included as an Appendix for readers who need tolearn or brush up on their Excel skills. Written in an informal, highly accessible style, this text is anexcellent guide to descriptive statistics, estimation, testinghypotheses, and model building.
The accessible style and focus onreal-life problem solving are perfectly suited to both students andpractitioners. The book emphasizes the discoverymethod, enabling readers to ascertain solutions on their own ratherthan simply copy answers or apply a formula by rote.
TheSecond Edition utilizes the R programming language to simplifytedious computations, illustrate new concepts, and assist readersin completing exercises. It contains dynamic graphics and allows students to manipulate data sets in order to visualize statistics and gain a deeper conceptual understanding about the meaning behind data.
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