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Learning Statistics with R

Author: Daniel Navarro

Publisher: Lulu.com

Published: 2013-01-13

Total Pages: 617

ISBN-13: 1326189727

"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

New Blueprints for Gains in Stocks and Grains & One-Way Formula for Trading in Stocks & Commodities

Author: William Dunnigan

Publisher: Harriman House Limited

Published: 2005-06-30

Total Pages: 290

ISBN-13: 1897597576

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Easy to use, and adopted by many successful traders over the years, William Dunnigan's One-Way Formula for Trading in Stocks and Commodities is a robust and reliable mechanical approach to buy/sell decision-making in speculative markets. A rare example of a 'universal' formula, this technique can be applied to almost any stock or commodity market, and requires little more than accurate line and bar charts.To understand the union of these two books, we have to understand the author's ambition to develop a complete trading system which gave exact buy/sell signals for stocks or commodities, which was mechanical in all its applications, and which didn't require the user to make any mental decisions.In New Blueprints for Gains in Stocks and Grains the author explores and introduces a full range of technical principles and lays the essential analytical groundwork for this universal formula.

Basic and Advanced Statistical Tests

Author: Amanda Ross

Publisher: Springer

Published: 2018-01-03

Total Pages: 10

ISBN-13: 9463510869

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This book focuses on extraction of pertinent information from statistical test outputs, in order to write result sections and/or accompanying tables and/or figures. The book is divided into two encompassing sections: Part I – Basic Statistical Tests and Part II – Advanced Statistical Tests. Part I includes 9 basic statistical tests, and Part II includes 7 advanced statistical tests. Each chapter provides the name of a basic or advanced statistical test, a brief description, examples of when to use each, a sample scenario, and a sample results section write-up. Depending on the test and need, most chapters provide a table and/or figure to accompany the write-up. The purpose of the book is to provide researchers with a reference manual for writing results sections and tables/figures in scholarly works. The authors fill a gap in research support manuals by focusing on sample write-ups and tables/figures for given statistical tests. The book assists researchers by eliminating the need to comb through numerous publications to determine necessary information to report, as well as correct APA format to use, at the close of analyses.

Introductory Business Statistics (hardcover, Full Color)

Author: Alexander Holmes

Publisher:

Published: 2023-06-30

Total Pages: 0

ISBN-13: 9781998109494

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Printed in color. Introductory Business Statistics is designed to meet the scope and sequence requirements of the one-semester statistics course for business, economics, and related majors. Core statistical concepts and skills have been augmented with practical business examples, scenarios, and exercises. The result is a meaningful understanding of the discipline, which will serve students in their business careers and real-world experiences.

Design of Experiments

Author: R. O. Kuehl

Publisher: Duxbury Resource Center

Published: 2000

Total Pages: 0

ISBN-13: 9780534368340

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"In this Second Edition of Design of Experiments: Statistical Principles of Research Design and Analysis, Bob Kuehl continues to treat research design as a very practical subject. He emphasizes the importance of developing a treatment design based on research hypothesis as an initial step and then developing an experimental or observational study design that facilitates efficient data collection. With the book's wide array of examples from actual studies from many scientific and technological fields, Kuehl constantly reinforces the research design process."--Back cover.

The Analysis of Variance

Author: Henry Scheffé

Publisher: John Wiley & Sons

Published: 1999-03-05

Total Pages: 500

ISBN-13: 9780471345053

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Originally published in 1959, this classic volume has had a major impact on generations of statisticians. Newly issued in the Wiley Classics Series, the book examines the basic theory of analysis of variance by considering several different mathematical models. Part I looks at the theory of fixed-effects models with independent observations of equal variance, while Part II begins to explore the analysis of variance in the case of other models.

Introductory Statistics 2e (hardcover, Full Color)

Author: Barbara Illowsky

Publisher:

Published: 2023-12-14

Total Pages: 0

ISBN-13: 9781998295470

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Book Publication Date: Dec 13, 2023. Full color. Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills.

Excel 2019 for Engineering Statistics

Author: Thomas J. Quirk

Publisher: Springer Nature

Published: 2020-04-09

Total Pages: 260

ISBN-13: 3030392783

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Newly revised to specifically address Microsoft Excel 2019, this book shows the capabilities of Excel in teaching engineering statistics effectively. Similar to the previously published Excel 2016 for Engineering Statistics, this volume is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical engineering problems. Excel, a widely available computer program for students and professionals, is also an effective teaching and learning tool for quantitative analyses in engineering courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Engineering Statistics capitalizes on these improvements by teaching readers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand engineering problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full practice test (with answers in an appendix) that allows readers to test what they have learned. This new edition features a wealth of new sample problems and solutions, as well as updated chapter content throughout.

Doing Meta-Analysis with R

Author: Mathias Harrer

Publisher: CRC Press

Published: 2021-09-15

Total Pages: 500

ISBN-13: 1000435636

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Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book

Using R for Introductory Statistics

Author: John Verzani

Publisher: CRC Press

Published: 2018-10-03

Total Pages: 522

ISBN-13: 1315360306

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The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.