Common Errors in Statistics (and How to Avoid Them), 2nd Edition + Introduction to Statistics Through Resampling Methods and Microsoft Office Excel - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Common Errors in Statistics (and How to Avoid Them), 2nd Edition + Introduction to Statistics Through Resampling Methods and Microsoft Office Excel write by Phillip I. Good. This book was released on 2008-03-14. Common Errors in Statistics (and How to Avoid Them), 2nd Edition + Introduction to Statistics Through Resampling Methods and Microsoft Office Excel available in PDF, EPUB and Kindle. This set contains: 9780471794318 Common Errors in Statistics (and How to Avoid Them), 2nd Edition and 9780471715757 Introduction to Statistics Through Resampling Methods and R/S Plus?? both by Phillip I. Good and James W. Hardin.
Erring Experts
Erring Experts - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Erring Experts write by Sally Agarwal. This book was released on 1988. Erring Experts available in PDF, EPUB and Kindle.
Introduction to Statistics Through Resampling Methods and Microsoft Office Excel
Introduction to Statistics Through Resampling Methods and Microsoft Office Excel - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Statistics Through Resampling Methods and Microsoft Office Excel write by Phillip I. Good. This book was released on 2005-07-22. Introduction to Statistics Through Resampling Methods and Microsoft Office Excel available in PDF, EPUB and Kindle. Learn statistical methods quickly and easily with the discovery method With its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers quickly master 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. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research, including: * Tests and estimation procedures for one, two, and multiple samples * Model building * Multivariate analysis * Complex experimental design Throughout the text, Microsoft Office Excel(r) is used to illustrate new concepts and assist readers in completing exercises. An Excel Primer is included as an Appendix for readers who need to learn or brush up on their Excel skills. Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. All the pedagogical tools needed to facilitate quick learning are provided: * More than 100 exercises scattered throughout the text stimulate readers' thinking and actively engage them in applying their newfound skills * Companion FTP site provides access to all data sets discussed in the text * An Instructor's Manual is available upon request from the publisher * Dozens of thought-provoking questions in the final chapter assist readers in applying statistics to solve real-life problems * Helpful appendices include an index to Excel and Excel add-in functions This text serves as an excellent introduction to statistics for students in all disciplines. The accessible style and focus on real-life problem solving are perfectly suited to both students and practitioners.
Common Errors in Statistics (and How to Avoid Them)
Common Errors in Statistics (and How to Avoid Them) - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Common Errors in Statistics (and How to Avoid Them) write by Phillip I. Good. This book was released on 2011-09-20. Common Errors in Statistics (and How to Avoid Them) available in PDF, EPUB and Kindle. Praise for the Second Edition "All statistics students and teachers will find in this book a friendly and intelligentguide to . . . applied statistics in practice." —Journal of Applied Statistics ". . . a very engaging and valuable book for all who use statistics in any setting." —CHOICE ". . . a concise guide to the basics of statistics, replete with examples . . . a valuablereference for more advanced statisticians as well." —MAA Reviews Now in its Third Edition, the highly readable Common Errors in Statistics (and How to Avoid Them) continues to serve as a thorough and straightforward discussion of basic statistical methods, presentations, approaches, and modeling techniques. Further enriched with new examples and counterexamples from the latest research as well as added coverage of relevant topics, this new edition of the benchmark book addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research. The Third Edition has been considerably expanded and revised to include: A new chapter on data quality assessment A new chapter on correlated data An expanded chapter on data analysis covering categorical and ordinal data, continuous measurements, and time-to-event data, including sections on factorial and crossover designs Revamped exercises with a stronger emphasis on solutions An extended chapter on report preparation New sections on factor analysis as well as Poisson and negative binomial regression Providing valuable, up-to-date information in the same user-friendly format as its predecessor, Common Errors in Statistics (and How to Avoid Them), Third Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.
Statistics
Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistics write by Michael J. Crawley. This book was released on 2005-05-06. Statistics available in PDF, EPUB and Kindle. Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. * Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. * Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. * The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. * Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. * Includes numerous worked examples and exercises within each chapter. * Accompanied by a website featuring worked examples, data sets, exercises and solutions: http://www.imperial.ac.uk/bio/research/crawley/statistics Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.
