Statistics for library and information services : a primer for using open source R software for accessibility and visualization

Bibliographic Information

Statistics for library and information services : a primer for using open source R software for accessibility and visualization

Alon Friedman

Rowman & Littlefield, c2016

  • : hardcover

Available at  / 2 libraries

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Includes bibliographical references and index

Description and Table of Contents

Description

Statistics for Library and Information Services, written for non-statisticians, provides logical, user-friendly, and step-by-step instructions to make statistics more accessible for students and professionals in the field of Information Science. It emphasizes concepts of statistical theory and data collection methodologies, but also extends to the topics of visualization creation and display, so that the reader will be able to better conduct statistical analysis and communicate his/her findings. The book is tailored for information science students and professionals. It has specific examples of dataset sets, scripts, design modules, data repositories, homework assignments, and a glossary lexicon that matches the field of Information Science. The textbook provides a visual road map that is customized specifically for Information Science instructors, students, and professionals regarding statistics and visualization. Each chapter in the book includes full-color illustrations on how to use R for the statistical model that particular chapter will cover. This book is arranged in 17 chapters, which are organized into five main sections: *the first section introduces research design and data collection; *the second section discusses basic statistical concepts, including descriptive, bivariate, time series, and regression analyses; *section 3 covers the subject of visualization creation using Open Source R; *section 4 covers decision making from the analysis; and *the last section provides examples and references. Every chapter illustrates how to use Open Source R and features two subsections for the major ideas of the chapter: its statistical model and its visual representation. The statistical model captures the main statistical formulas/theories covered in each chapter, while the visual representation addresses the subject of the types of visualization that are produced from the statistical analysis model covered in that particular chapter. Don't miss the book's companion Web site at www.statisticsforlis.org

Table of Contents

Part I INTRODUCTION TO STATISTICS CHAPTER 1 Introduction CHAPTER 2 Research Design CHAPTER 3 Data (Types and Collection Methods) CHAPTER 4 How to Run R Part II MAKING SENSE OF STATISTICS CHAPTER 5 Descriptive statistics CHAPTER 6 Bivariate Statistics CHAPTER 7 Probability Theory CHAPTER 8 Random Variables and Probability Distributions CHAPTER 9 Sampling Distributions CHAPTER 10 Confidence Interval Estimation CHAPTER 11 Fundamentals of Hypothesis Testing CHAPTER 12 Correlation and Regression CHAPTER 13 Analysis of Variances and Chi-square Tests CHAPTER 14 Time Series and Predictive Analytics Part III VISUALIZATION IN R CHAPTER 15 Visualization Display CHAPTER 16 Advanced Visualization Display CHAPTER 17 Applying visualization to statistics analysis APPENDIX A Frequency used formulas used in this book APPENDIX B Frequency R commands APPENDIX C References

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