{"product_id":"veridical-data-science-isbn-9780262049191","title":"Veridical Data Science","description":"\u003cb\u003eUsing real-world data case studies, this innovative and accessible textbook introduces an actionable framework for conducting trustworthy data science.\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eMost textbooks present data science as a linear analytic process involving a set of statistical and computational techniques without accounting for the challenges intrinsic to real-world applications. \u003ci\u003eVeridical Data Science\u003c\/i\u003e, by contrast, embraces the reality that most projects begin with an ambiguous domain question and messy data; it acknowledges that datasets are mere approximations of reality while analyses are mental constructs. \u003cbr\u003eBin Yu and Rebecca Barter employ the innovative Predictability, Computability, and Stability (PCS) framework to assess the trustworthiness and relevance of data-driven results relative to three sources of uncertainty that arise throughout the data science life cycle: the human decisions and judgment calls made during data collection, cleaning, and modeling. By providing real-world data case studies, intuitive explanations of common statistical and machine learning techniques, and supplementary R and Python code, \u003ci\u003eVeridical Data Science\u003c\/i\u003e offers a clear and actionable guide for conducting responsible data science. Requiring little background knowledge, this lucid, self-contained textbook provides a solid foundation and principled framework for future study of advanced methods in machine learning, statistics, and data science. \u003cbr\u003e\u003cbr\u003e\u003cul\u003e\n\u003cli\u003ePresents the Predictability, Computability, and Stability (PCS) methodology for producing trustworthy data-driven results\u003c\/li\u003e\n\u003cli\u003eTeaches how a data science project should be conducted from beginning to end, including extensive discussion of the data scientist's decision-making process\u003c\/li\u003e\n\u003cli\u003eCultivates critical thinking throughout the entire data science life cycle\u003c\/li\u003e\n\u003cli\u003eProvides practical examples and illuminating case studies of real-world data analysis problems with associated code, exercises, and solutions\u003c\/li\u003e\n\u003cli\u003eSuitable for advanced undergraduate and graduate students, domain scientists, and practitioners\u003c\/li\u003e\n\u003c\/ul\u003eContents vii\u003cbr\u003eAcknowledgments xv\u003cbr\u003ePreface xvii\u003cbr\u003eI PART 1: AN INTRODUCTION TO VERIDICAL DATA SCIENCE 1\u003cbr\u003e1 An introduction to veridical data science 3\u003cbr\u003e2 The Data Science Life Cycle 23\u003cbr\u003e3 Setting up your data science project 43\u003cbr\u003eII PART 2: PREPARING, EXPLORING, AND DESCRIBING DATA 65\u003cbr\u003e4 Data Preparation 67\u003cbr\u003e5 Exploratory Data Analysis 109\u003cbr\u003e6 Principal component analysis 149\u003cbr\u003e7 Clustering 197\u003cbr\u003eIII PART 3: PREDICTION 253\u003cbr\u003e8 An introduction to prediction problems 255\u003cbr\u003e9 Predicting continuous responses with Least Squares 275\u003cbr\u003e10 Extending the Least Squares algorithm 311\u003cbr\u003e11 Predicting binary responses and logistic regression 353\u003cbr\u003e12 Decision trees and random forest 403\u003cbr\u003e13 Producing the final prediction results 437\u003cbr\u003e14 Conclusion 473\u003cbr\u003eAnswers to True or False exercises 481\u003cb\u003eBin Yu\u003c\/b\u003e is Chancellor's Distinguished Professor and Class of 1936 Second Chair in Statistics, EECS, and Computational Biology at the University of California, Berkeley, a 2006 Guggenheim Fellow, and a member of the US National Academy of Sciences and the American Academy of Arts and Sciences.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eRebecca L. Barter\u003c\/b\u003e is Research Assistant Professor in Epidemiology at the University of Utah.","brand":"The MIT Press","offers":[{"title":"Default Title","offer_id":44865451098341,"sku":"NP9780262049191","price":80.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780262049191.jpg?v=1767743417","url":"https:\/\/k12savings.com\/products\/veridical-data-science-isbn-9780262049191","provider":"K12savings","version":"1.0","type":"link"}