«'I know of few books about data analysis and visualization that are as comprehensive, deep, practical, and current as this one; and I know of almost none that are as fun to read. Gábor Békés and Gábor Kézdi have created a most unusual and most compelling beast: a textbook that teaches you the subject matter well and that, at the same time, you can enjoy reading cover to cover.' Alberto Cairo, University of Miami»

«'A beautiful integration of econometrics and data science that provides a direct path from data collection and exploratory analysis to conventional regression modeling, then on to prediction and causal modeling. Exactly what is needed to equip the next generation of students with the tools and insights from the two fields.' David Card, University of California, Berkeley, winner of the Nobel Memorial Prize in Economic Sciences»

«'A multifaceted book that considers many sides of data analysis, all of them important for the contemporary student and practitioner. It brings together classical statistics, regression, and causal inference, sending the message that awareness of all three aspects is important for success in this field. Many 'best practices' are discussed in accessible language, and illustrated using interesting datasets.' llya Ryzhov, University of Maryland»

«'This textbook is excellent at dissecting and explaining the underlying process of data analysis. Békés and Kézdi have masterfully woven into their instruction a comprehensive range of case studies. The result is a rigorous textbook grounded in real-world learning, at once accessible and engaging to novice scholars and advanced practitioners alike. I have every confidence it will be valued by future generations.' Kerwin K. Charles, Yale School of Management»

«'This book takes you by the hand in a journey that will bring you to understand the core value of data in the fields of machine learning and economics. The large amount of accessible examples combined with the intuitive explanation of foundational concepts is an ideal mix for anyone who wants to do data analysis. It is highly recommended to anyone interested in the new way in which data will be analyzed in the social sciences in the next years.' Christian Fons-Rosen, Barcelona Graduate School of Economics»

«'This sophisticatedly simple book is ideal for undergraduate- or Master's-level Data Analytics courses with a broad audience. The authors discuss the key aspects of examining data, regression analysis, prediction, Lasso, and random forests, and more, with using elegant prose instead of algebra. Using well-chosen case studies, they illustrate the techniques and discuss all of them patiently and thoroughly.' Carter Hill, Louisiana State University»

«'This is not an econometrics textbook. It is a data analysis textbook. And a highly unusual one - written in plain English, based on simplified notation, and full of case studies. An excellent starting point for future data analysts or anyone interested in finding out what data can tell us.' Beata Javorcik, University of Oxford»

«'This is a fantastic book to have. Strong data skills are critical for modern business and economic research, and this text provides a thorough and practical guide to acquiring them. Highly recommended.' John van Reenen, MIT Sloan»

«'Energy and climate change is one of the most important public policy challenges, and high- quality data and its empirical analysis is a foundation of solid policy. Data Analysis for Business, Economics, and Policy will make an important contribution to this with its innovative approach. In addition to the comprehensive treatment of modern econometric techniques, the book also covers the less glamorous but crucial aspects of procuring and cleaning data, and drawing useful inferences from less-than-perfect datasets. As the center of gravity of the energy system shifts to developing economies where data quality is still an issue, this will provide an important and practical combination for both academic and policy professionals.' Laszlo Varro, Chief Economist, International Energy Agency»

«'This exciting new text covers everything today's aspiring data scientist needs to know, managing to be comprehensive as well as accessible. Like a good confidence interval, the Gabors have got you almost completely covered!' Joshua Angrist, Massachusetts Institute of Technology, winner of the Nobel Memorial Prize in Economic Sciences»

«'This is an excellent book for students learning the art of modern data analytics. It combines the latest techniques with practical applications, replicating the implementation side of classroom teaching that is typically missing in textbooks. For example, they used the World Management Survey data to generate exercises on firm performance for students to gain experience in handling real data, with all its quirks, problems, and issues. For students looking to learn data analysis from one textbook, this is a great way to proceed.' Nicholas Bloom, Stanford University»