Why am I passionate about this?

I was trained as a mathematician but have always been motivated by problem-solving challenges. Statistics and analytics combine mathematical models with statistical thinking. My career has always focused on this combination and, as a statistician, you can apply it in a wide range of domains. The advent of big data and machine learning algorithms has opened up new opportunities for applied statisticians. This perspective complements computer science views on how to address data science. The Real Work of Data Science, covers 18 areas (18 chapters) that need to be pushed forward in order to turning data into information, better decisions, and stronger organizations


I wrote

The Real Work of Data Science: Turning Data into Information, Better Decisions, and Stronger Organizations

By Ron S. Kenett, Thomas C. Redman,

Book cover of The Real Work of Data Science: Turning Data into Information, Better Decisions, and Stronger Organizations

What is my book about?

Data and data science can be truly transformative, improving customer satisfaction, increasing profits, and empowering people. The book is about…

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The books I picked & why

Book cover of Computer Age Statistical Inference, Algorithms, Evidence, and Data Science

Ron S. Kenett Why did I love this book?

The text covers classic statistical inference, early computer-age methods, and twenty-century topics. This puts a unique perspective on current analytic technologies labeled machine learning, artificial intelligence, and statical learning. The examples used provide a powerful description of the methods covered and the compare and contrast sections highlight the evolution of analytics. This book by Efron and Hastie is a natural follow-up source for readers interested in more details.

By Bradley Efron, Trevor Hastie,

Why should I read it?

2 authors picked Computer Age Statistical Inference, Algorithms, Evidence, and Data Science as one of their favorite books, and they share why you should read it.

What is this book about?

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. 'Data science' and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? How does it all fit together? Now in paperback and fortified with exercises, this book delivers a concentrated course in modern statistical thinking. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic…


Book cover of The Book of Why: The New Science of Cause and Effect

Ron S. Kenett Why did I love this book?

Causality is a topic that has been of interest for centuries. Statisticians have been careful to emphasize that correlation is not causation as lurking variables can show apparent relationships which are misleading. The first author is a main force behind modern efforts to address causality models. He developed graphical representations linking variables and a method of intervention, called the “do” calculus, which enables the study of causal effects in observed data. The historical perspective provided in the book makes it an excellent reference to anyone interested in the topic.

By Judea Pearl, Dana MacKenzie,

Why should I read it?

6 authors picked The Book of Why as one of their favorite books, and they share why you should read it.

What is this book about?

'Wonderful ... illuminating and fun to read'
- Daniel Kahneman, winner of the Nobel Prize and author of Thinking, Fast and Slow

'"Pearl's accomplishments over the last 30 years have provided the theoretical basis for progress in artificial intelligence and have redefined the term "thinking machine"'
- Vint Cerf, Chief Internet Evangelist, Google, Inc.

The influential book in how causality revolutionized science and the world, by the pioneer of artificial intelligence

'Correlation does not imply causation.' This mantra was invoked by scientists for decades in order to avoid taking positions as to whether one thing caused another, such as smoking…


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Book cover of We Had Fun and Nobody Died: Adventures of a Milwaukee Music Promoter

We Had Fun and Nobody Died By Amy T. Waldman, Peter Jest,

This irreverent biography provides a rare window into the music industry from a promoter’s perspective. From a young age, Peter Jest was determined to make a career in live music, and despite naysayers and obstacles, he did just that, bringing national acts to his college campus atUW-Milwaukee, booking thousands of…

Book cover of The Undoing Project: A Friendship That Changed Our Minds

Ron S. Kenett Why did I love this book?

In addressing decision makers, an understanding of forces affecting human behavior is essential. The author provides a comprehensive view on the work of Kahneman and Tversky mapping their journey which lead to their highly impactful behavioral economic body of knowledge. The bias they address provides data scientists a widened perspective on their role and how to address organizational challenges. This provides a language to recognise and address bias inherent in human thinking. The book provides a very powerful set of tools for data scientists who want to see behind the numbers and understand forces affecting human behavior.

By Michael Lewis,

Why should I read it?

6 authors picked The Undoing Project as one of their favorite books, and they share why you should read it.

What is this book about?

'Michael Lewis could spin gold out of any topic he chose ... his best work ... vivid, original and hard to forget' Tim Harford, Financial Times

'Gripping ... There is war, heroism, genius, love, loss, discovery, enduring loyalty and friendship. It is epic stuff ... Michael Lewis is one of the best non-fiction writers of our time' Irish Times

From Michael Lewis, No.1 bestselling author of The Big Short and Flash Boys, this is the extraordinary story of the two men whose ideas changed the world.

Daniel Kahneman and Amos Tversky met in war-torn 1960s Israel. Both were gifted young…


Book cover of Out of the Crisis

Ron S. Kenett Why did I love this book?

The book refers to the crisis in western industrialized countries in the 1980s. It emphasizes the role of management and the focus on processes for inducing changes and improvements. Deming, a statistician and physicist by training, moved his attention to management consulting, as a necessary step to ensure results and enhanced impact. The Deming message needs to be updated to the big data analytic era. Modern data scientists have powerful analytics and immense data sets to work with. They can significantly contribute to their organization’s bottom line by improving quality, productivity, and competitive performance. Deming’s book provides a context for making this happen.

By W. Edwards Deming,

Why should I read it?

3 authors picked Out of the Crisis as one of their favorite books, and they share why you should read it.

What is this book about?

Essential reading for managers and leaders, this is the classic work on management, problem solving, quality control, and more—based on the famous theory, 14 Points for Management

In his classic Out of the Crisis, W. Edwards Deming describes the foundations for a completely new and transformational way to lead and manage people, processes, and resources. Translated into twelve languages and continuously in print since its original publication, it has proved highly influential. Research shows that Deming’s approach has high levels of success and sustainability. Readers today will find Deming’s insights relevant, significant, and effective in business thinking and practice. This…


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Book cover of Ambidextrous: The Secret Lives of Children

Ambidextrous By Felice Picano,

Bold, funny, and shockingly honest, Ambidextrous is like no other memoir of 1950s urban childhood.

Picano appears to his parents and siblings to be a happy, cheerful eleven-year-old possessed of the remarkable talent of being able to draw beautifully and write fluently with either hand. But then he runs into…

Book cover of Information Quality: The Potential of Data and Analytics to Generate Knowledge

Ron S. Kenett Why did I love this book?

A lightly technical introduction to a comprehensive framework defining and evaluating the quality of information generated by statistical analysis. It expands the role of analytics by including dimensions that affect information quality such as data resolution, data integration, operationalization, and generalizability of findings. This wide-angle perspective provides a practical checklist that has been found useful in applications. Multiple case studies enable the reader to connect to his favorite topic, but also learn from other areas.

By Ron S. Kenett, Galit Shmueli,

Why should I read it?

1 author picked Information Quality as one of their favorite books, and they share why you should read it.

What is this book about?

Provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis Analytics and statistical analysis have become pervasive topics, mainly due to the growing availability of data and analytic tools. Technology, however, fails to deliver insights with added value if the quality of the information it generates is not assured. Information Quality (InfoQ) is a tool developed by the authors to assess the potential of a dataset to achieve a goal of interest, using data analysis. Whether the information quality of a dataset is sufficient is of practical importance…


Explore my book 😀

The Real Work of Data Science: Turning Data into Information, Better Decisions, and Stronger Organizations

By Ron S. Kenett, Thomas C. Redman,

Book cover of The Real Work of Data Science: Turning Data into Information, Better Decisions, and Stronger Organizations

What is my book about?

Data and data science can be truly transformative, improving customer satisfaction, increasing profits, and empowering people. The book is about turning numbers into information and insights. To be useful, the data analysis needs to guide decisions that carry a positive impact in the workplace. The chapters cover the different steps data scientists take in organizations. Eighteen short chapters provide, with case studies, essential elements that characterize the data transformation leveraging numbers into information. It is a blueprint for the role of data scientists in organizations. Both data scientists and their managers can benefit from it.

Book cover of Computer Age Statistical Inference, Algorithms, Evidence, and Data Science
Book cover of The Book of Why: The New Science of Cause and Effect
Book cover of The Undoing Project: A Friendship That Changed Our Minds

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