846 pages | October 2023 | Quadrangle
Preface | Contents | Index | Datasets
DUDADS Volumes: [1 | 2 | 3 | 4 | 5 | PDV]
P. Boily and J. Schellinck (with contributions from K. Cheung, A. Crowther, C. Ma, and E. Ghashim)
Chapter 02: Multivariate Calculus for Data Analysis (40 pages)
F. Donzelli and P. Boily
Chapter 03: Overview of Linear Algebra (34 pages)
F. Donzelli (with contributions by P. Boily)
Chapter 04: Basics of Numerical Methods (46 pages)
P. Boily (inspired by D. Guignard)
Chapter 05: A Survey of Optimization (26 pages)
P. Boily and K. Cheung
Chapter 06: Probability and Applications (84 pages)
P. Boily (inspired by R. Kulik)
Chapter 07: Introductory Statistical Analysis (72 pages)
P. Boily (with contributions from S. Hagiwara)
Chapter 08: Classical Regression Analysis (82 pages)
P. Boily (inspired by G. Lamothe)
Chapter 09: Time Series and Forecasting (108 pages)
P. Boily (inspired by R. Kulik)
Chapter 10: Survey Sampling Methods (134 pages)
P. Boily (inspired by P. Farrell)
Chapter 11: The Design of Experiments (70 pages)
P. Boily (inspired by D. Haziza)
Chapter 12: Simulations and Modeling (23 pages)
J. Schellinck and P. Boily
Back Cover Description: "Embark on a multidisciplinary journey into the fascinating realm of data science with Volume 1 of Patrick Boily's Data Understanding, Data Analysis, and Data Science series. Crafted in collaboration with practitioners and leading scholars, this groundbreaking tome is more than a 'book' -- it's your go-to reference manual, filled with examples, exercises, and hands-on applications.
Dive into the core principles of programming, then explore specialized topics such as numerical methods, probability theory, and survey sampling. From fundamental concepts to advanced techniques, Prelude to Data Understanding offers an immersive, tool-agnostic approach designed to cultivate true comprehension, not just rote learning.
Discover why data science is a dynamic field influenced by analytic choices, and why understanding its complexities is not just a task but an ongoing adventure. Whether you're a student, a professional, or simply a curious mind, this is the ultimate guide to gaining a well-rounded grasp of data's multifaceted nature.
Perfect for parallel reading alongside guided lectures or for independent study, this robust volume is your first step into a world where data is not just numbers, but a story waiting to be told."