Incredulous stares. Conversations cease as a hush falls over the room. Small children stop crying and tilt their heads sideways. “You read a book? …For fun? When?” Yes, this is the likely reaction that you’ll receive after announcing that you read something longer than a case study from cover to cover while dealing with the workload of grad school. Or so I would imagine. Most of the time our eyes are glued to our computer or phone screens, jumping from Python codes, R scripts, and Excel sheets to emails and Twitter feeds, skimming posts and titles, making mental notes to read something later before rushing off to work on the next project and completely forgetting about whatever article piqued our interest. Fortunately, the wonderful professors and staff here in charge of the MSBA program didn’t get to where they are by sitting on their hands, and have decided to share a few of their favorites (both non-fiction literature and textbooks). These recommendations are based on the simple criterion of being well written or enjoyable, while tying back to any one of the many topics related to analytics.

 

So whether you’re buried under a few feet of snow with nothing but Wi-fi and your Kindle to keep you company, or just looking for a few pieces to add to your summer reading list, make sure to give these titles a look! (And if you’re an incoming student hoping to improve your analytics chops, any one of these is be a great place to start.)

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Competing on Analytics: The New Science of Winning by Tom Davenport:

“This book describes organizations that use business intelligence and analytics not only to improve operations, but also to compete more effectively” (from tomdavenport.com).

 

 

The Price of Everything: Solving the Mystery of Why We Pay What We Do by Eduardo Porter:

“The Price of Everything starts with a simple premise: there is a price behind each choice that we make, whether we’re deciding to have a baby, drive a car, or buy a book. We often fail to appreciate just how critical prices are as a motivating force shaping our lives. But their power becomes clear when distorted prices steer our decisions the wrong way” (from eduardoporter.com).

 

Investment Science by David Luenberger:

“Investment Science, (a textbook), provides thorough and highly accessible mathematical coverage of the fundamental topics of intermediate investments, including fixed-income securities, capital asset pricing theory, derivatives, and innovations in optimal portfolio growth and valuation of multi-period risky investments” (from amazon.com).

 

 

Mostly Harmless Econometrics: An Empiricist’s Companion by Joshua Angrist:

“In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions — regression discontinuity designs and quantile regression — as well as how to get standard errors right. Angrist and Pischke explain why fancier techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science” (from mostlyharmlesseconometrics.com).

 

Bayesian Statistics and Marketing by Peter Rossi, Greg Allenby, & Rob McCulloch:

            “Bayesian Statistics and Marketing describes the basic advantages of the Bayesian approach, detailing the nature of the computational revolution. Examples contained include household and consumer panel data on product purchases and survey data, demand models based on micro-economic theory and random effect models used to pool data among respondents. The book also discusses the theory and practical use of MCMC methods” (from wiley.com).

 

The Wisdom of the Crowds by James Surowiecki:

“The Wisdom of the Crowds is about the aggregation of information in groups, resulting in decisions that, arguably, are often better than could have been made by any single member of the group. It presents numerous case studies and anecdotes to illustrate its argument, and touches on several fields, primarily economics and psychology” (from wikipedia.org).

 

 

Of course, no reading list on analytics would be complete without two of the most well known mainstream works:

 

Moneyball: The Art of Winning an Unfair Game by Michael Lewis:

“Moneyball is a quest for the secret of success in baseball. In a narrative full of fabulous characters and brilliant excursions into the unexpected, Michael Lewis follows the low-budget Oakland A’s, visionary general manager Billy Beane, and the strange brotherhood of amateur baseball theorists. They are all in search of new baseball knowledge – insights that will give the little guy who is willing to discard old wisdom the edge over big money” (from michaellewiswrites.com).

 

The Signal and the Noise by Nate Silver:

“Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the “prediction paradox”: The more humility we have about our ability to make predictions, the more successful we can be in planning for the future” (from amazon.com).

 

And remember, a number of areas in the analytics world are constantly evolving. By the time a book is published on a given topic, it may already be old news. Make sure to keep up with blogs, articles, research papers, and of course, @TexasAnalytics on Twitter.

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Happy reading!

(A special thanks to Professors Hasler, Sonnier, Barua, Rao, & Muthuraman for their help in compiling this list)