Data Analysis for Business, Economics, and Policy

by Gábor Békés, Gábor Kézdi

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.

Genres: Nonfiction, Business

730 pages, Kindle Edition

Published May 6, 2021

Reviews

[Anna Bárdits · Rating 5 out of 5]

I've had the chance to attend a course of one of the authors Gábor Kézdi during my MA studies at the Central European University. Kézdi was the one of the best teachers I've ever had, and attending his course was challanging and fun at the same time. I could almost hear his words when I read this book: clear, intelligent and interesting explanations of even the hardest concepts.
The text is always intuitive and practical, using very minimal maths, but staying precise nevertheless.
I think the best thing in this book is that it is honest and clear about the whole process of data analyis, ackowledging that most of the time you have to deal with dirty data, and a huge part of data analysis is making decisons about the data itself (what to do with outliers, missing values, etc). Also, the book emphasises that there is not a single good answer when you analyze data, you have to make choices and you have to be transparent when you make those choices.
A very good textbook, also suitable if you want to learn data analysis by yourself. Lots of codes and free datasets are provided, so you can easily practice. You can learn descriptive analysis, causal analysis, machine learning techniques, etc. All in all, an excellent book!

[Brigitta · Rating 3 out of 5]

Az egyetemen volt egy 'Bevezetés az empirikus közgazdaságtanba' tantárgyam, amelyhez ennek a könyvnek a magyar fordítása szolgált tankönyvként. Mondanom sem kell, hogy nem a legolvasmányosabb mű, viszont tudott segíteni a tárgy megértésében. Részletes, alapos, és az esettanulmányok hasznosak az értelmezéshez (már ha nem ugorja át őket az ember). Bár összességében jó szakirodalom, időnként akadtak benne nehezen értelmezhető, kissé túlbonyolított részek is. Én mélyen fellélegeztem, amikor 'motorháztető alatti' oldalakhoz értem (- szemrebbenés nélkül lapoztam át), de akiket mélyebben érdekelnek az egyenletek, modellek matematikai háttere, azoknak tetszhet. Inkább tanuláshoz való, mint élvezetes olvasmánynak.

[Mihaly Borsi · Rating 5 out of 5]

An excellent, non-technical book that can be perfectly used to provide basic econometrics knowledge to PhD students with a very diverse background (Business, Economics, Public policy). Complementary case studies with corresponding codes are also available (for free)!

5/5!