Get Ready for Data Science

Rex B. Kline, PhD, is Professor of Psychology at Concordia University in Montréal, Québec, Canada. Since earning a doctorate in clinical psychology, Dr. Kline has conducted research on the psychometric evaluation of cognitive abilities, behavioral and scholastic assessment of children, structural equation modeling, training of researchers, statistics reform in the behavioral sciences, and usability engineering in computer science. He has published a number of chapters, journal articles, and books in these areas.

“This book offers a thorough, accessible introduction to key concepts in data science, combining theoretical grounding with practical application. It includes clear explanations, code examples, and exercises that will benefit both students and professionals looking to strengthen their data science knowledge. Placing supervised and unsupervised machine learning later in the book allows readers to build the necessary intuition and technical foundations before tackling complex models. Kline does an excellent job balancing depth with clarity. The emphasis on conceptual understanding adds pedagogical value.--Nir Kshetri, PhD, Department of Management, University of North Carolina at Greensboro“This text offers a comprehensive, well-structured overview of key data science concepts, bridging traditional statistical thinking with modern machine learning and computational approaches. The examples, figures, and appendices provide meaningful reinforcement of the chapter content, contributing significantly to the book's instructional value. Code examples are well annotated and easy to follow, with clear flow that reflects careful attention to reader comprehension. I commend the author for his thoughtful integration of code and narrative (which is no small task!).â€--Sarah Depaoli, PhD, Department of Psychological Sciences, University of California, MercedGet Ready for Data Science is the most comprehensive data science book available for behavioral science students and professionals. The narrative writing style is a strong feature of the text. The R code and output figures with detailed interpretation help students learn how to implement the analytical techniques and interpret the outputs.â€--Toshiyuki Yuasa, PhD, Hobby School of Public Affairs, University of Houston“I appreciate that Kline begins by providing foundational knowledge and developing the reader's understanding of up-to-date statistical methods, rather than jumping right into tools and technical skills. The coverage of topics is excellent--I would recommend this book to any early-career researcher.â€--Glenn Williams, PhD, School of Psychology, Northumbria University, United Kingdom-

• IntroductionI. Classical Statistics and Data Science1. Ready Set Go2. Classical Statistics3. Data ScienceII. Dispelling Myth and Alternatives4. Estimating Uncertainty5. Avoiding Insignificance6. Lessons from Regression7. Bayesian BasicsIII. Programming and Data8. Programming9 Data Visualization10. Big Data11. Data ReductionIV. Machine Learning and Beyond12. Supervised Machine Learning: Core Methods13. Supervised Machine Learning: Hyperparameter Tuning14. Supervised Machine Learning: Complex Effects15. Unsupervised Machine Learning16. Other Data Science HorizonsSuggested Answers to ExercisesReferencesAuthor IndexSubject IndexAbout the Author