Preface

While a research assistant at Academia Sinica, one of my responsibilities was called the “Statistics Clinics,” where I provided statistical consulting to researchers. I noticed that many researchers frequently asked the same fundamental questions, such as those about t-tests or ANOVA. Each time I explained these concepts, I had to repeatedly open the same website to illustrate the correct ideas and guide them step-by-step through interpreting results or applying methods correctly. While important, this repetitive process gradually became tedious. One day, it struck me: “Why not write a book?” Doing so allowed me to consolidate these explanations into a single resource, saving time and effort for future consultations.

I view this book as more of a personal set of notes, so the structure might not be perfectly organized. I wrote it progressively, starting with elementary concepts and advancing to highly complex topics. I believe the most straightforward sections can be understood by senior high school students, while the most challenging parts may require a solid grasp of higher mathematics, including (advanced) calculus, linear algebra, scientific computing, and real analysis.

This book covers a comprehensive range of statistics and data analysis topics, starting with Part I: Foundations such as basic statistical concepts and mathematical statistics. It then progresses through Part II: Methodology - Beginner, introducing core statistical techniques like probability models, regression analysis, and time series analysis, before advancing to more complex methods in Part III: Methodology - Advanced, including generalized linear models, Bayesian analysis, and high-dimensional data analysis. The book also explores specialized statistical approaches in Part IV: Methodology - Others, such as nonparametric methods and directional statistics. Next are applications in Part V: Biostatistics and Part VI: Industrial Statistics, addressing fields like clinical trials, quality control, and experimental design. Additionally, it dives into various applications in Part VII: Other Fields, including operations research, financial statistics, and social statistics.

A focus on Part VIII: Computational Statistics introduces machine learning, statistical computing, and deep learning techniques, while Part IX: Computer Science Skills cover data structures, algorithms, and big data analytics. The book also emphasizes Part X: Data Communication with data processing, visualization, and mining techniques, and Part XI: Modern Data Analysis includes cutting-edge fields such as network, semantic, and image analysis. Part XII: Data Workflow teaches data management and integration, while Part XIII: Statistical Theory delves into statistical inference and probability theory. Finally, Part XIV: Miscellaneous topics cover statistical education and R advanced programming, ensuring a holistic understanding of statistics from theory to practical application.

Acknowledgement

Because there are too many people to thank, let’s just thank God. - 陳之藩《謝天》

Progress of this book

I’m still writing the book. Here are some notes on what part I have finished.

Chapter 1 almost complete (80%)

Chapter 2 in work

Future Work:

  1. Responsive Web Design (RWD): Implement Responsive Web Design to ensure the bookdown project is accessible and user-friendly across devices of different sizes.

  2. Mandarin version: Develop a Mandarin version of this bookdown project.