Description
Book SynopsisStatistics 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
Trade ReviewDr. Friedman’s book arrives at the right time as library and information professionals begin to grapple with the complexities of big data. This well-written and clearly organized primer will be a valuable addition to the LIS curriculum - it is clearly the moment for us to have a textbook that introduces statistics and an open source statistical computing language for our students and for information professionals from an “insider” who knows our field well. -- Howard Rosenbaum, Professor of Information Science and Associate Dean for Graduate Studies, Department of Information and Library Science, Indiana University
Table of ContentsPart 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
