Showing posts sorted by relevance for query Steven D. Levitt. Sort by date Show all posts
Showing posts sorted by relevance for query Steven D. Levitt. Sort by date Show all posts

Sunday, August 23, 2015

Freakonomics by Steven D. Levitt & Stephen J. Dubner

Economist Steven D. Levitt and journalist Stephen J. Dubner look into the unexpected relationships between aspects of our society in their book Freakonomics. They not particularly interested in the things you might expect economists to write about such as business, markets or investment. Instead, they look at cheating, crime, expertise and parenting.

There is no particular theme of the book, except possibly that common explanations and expectations are often off the mark. Levitt and Dubner are skeptical of conventional wisdom and expertise. They are interested in data and what questions can properly be put to that data.

They sometimes come to conclusions that some might find disturbing or troubling. For instance, they trace the drop in crime rates in the 1990s to the legalization of abortion in the 1970s. Many of the women who had abortions in the wake of Roe vs. Wade were poor, had low education, or very young. All of these traits in the parents tend to produce worse outcomes for children, including a higher likelihood of committing crime. As the first post-Roe cohort of children reached their teen years in the 1990s, there were fewer who had been raised in those conditions that may have pushed them into crime, and therefore fewer budding criminals and a decline in crime rates.

Reading this made me think of the arguments of eugenicists. They believed that a host of social ills, including crime, could be mitigated by keeping the unfit people from reproducing. To the eugenicists, unfit was essentially equivalent to nonwhite, though it also extended to the feebleminded (a disease a eugenically-minded psychiatrist or psychologist might have found in any poor, uneducated person). The eugenicists saw intelligence, criminality, poverty and host of other features as fixed and hereditary. Limiting the reproduction of the unfit through abortion or sterilization would reduce and eventually eliminate poverty and crime.

Of course, Levitt and Dubner are not eugenicists. Nor do they propose abortion as means to reduce crime. Crime does not have its roots in race or intelligence. It is strongly tied to poverty and low education. Charles Dickens chilling portrayed Ignorance and Want in A Christmas Carol, and they are still a threat to all of us.

Each chapter reveals an interesting twist on some subject, though few are as potentially charged as that on crime. In another chapter, the authors show that crime does not pay, except for those at the top, on unlike in a corporation. In spite of faddish thoughts on the issue, parents matter, though maybe not in the ways we’d like to think.

My previous reading has inclined me to focus on the darkest part of the book, but the overall tone is conversational and light, though the authors are not flippant about serous subjects. They are not technical either. Their use of statistics is straightforward. They do not delve deep into theory, though they focus much on the central theory of economics that people respond to incentives.

If you’re interested in this book, you may also be interested in


Levitt, Steven D., & Stephen J. Dubner. Freakonomics: A Rogue Economist Explores the Hidden Side of Everything. New York: William Morrow, 2005.

Wednesday, June 3, 2020

Range by David Epstein

Specialization is king. It has become seen as the road to success. Since Malcolm Gladwell popularized the 10,000-hour Rule a few years ago (perhaps unintentionally), I’ve seen a lot of people using it to justify and spell out the road to specialization: focus and start early. However, specialization can hurt when we face problems that cross boundaries and pull us out of our niche; we can be lost and ill equipped outside of our specialization. Journalist David Epstein explored the issue in his book, Range.

 Epstein starts out by showing the limitations of specialization. It works well in an arena where repeating patterns prevail, and we can learn to recognize those patterns from exposure. When there are no repeating patterns, or they are complex and obscure, a high degree of specialized knowledge can lead to wrong conclusions and false confidence. We can have a few good tools that we trust, but if they are the wrong tools for the job we may be doing the wrong thing without realizing it. Complex environments and problems require us to reason conceptually, connect ideas from different contexts and solve problems without direct prior knowledge of what we are facing. We need breadth.

 Though it is not as popular a narrative, Epstein provides several examples of how people with broad and diverse knowledge have become high achievers. Creativity is, to a great extent, finding relationships between seemingly unrelated things. One must be equipped with a variety of experience to be able to make these leaps.

 I can see how the generalist’s path can seem unappealing. It may not seem like a path at all. Deep learning is slow and effortful. It is a way of errors, false starts and diversions that can seem like a waste of time. Developing range is messy and uncertain; by comparison, specialization seems like a sure thing.

 Epstein’s book contains ways to develop range. Analogies allow us to apply knowledge from one area to another, and seeing where analogies fall apart can lead to new ideas. Take an outsider’s cooler, distant and critical view and save yourself from the pitfall of taking a rosy view of familiar things. Pay attention to things that don’t fit the model. Don’t plan too far ahead, but be open to exploration an experimentation. There is a time for mastering particular knowledge and procedure, but the overall approach to learning should be to make connections and gain perspective.

 If you’re interested in this book, you may also be interested in

The Checklist Manifesto by Atul Gawande

The First 20 Hours by Josh Kaufman

Freakonomics by Steven D. Levitt & Stephen J. Dubner

The Genius in All of Us by David Shenk

Learn Better by Ulrich Boser

Outliers by Malcolm Gladwell

 Epstein, David. Range: Why Generalists Triumph in a Specialized World. New York: Riverhead Books, 2019.


Saturday, April 17, 2021

Loserthink by Scott Adams

 America is awash in debate, but it seems there is very little actual discussion or argument happening. Many talk by each other and simply become more entrenched in their positions, or they adopt more extreme, outrageous or nonsensical views. It does not help that politicians and pundits engage in the same kind of thing and seem to encourage it in others. In addition, television and radio broadcasts are full of it, propagating the noise, perhaps emphasizing one side or the other, but rarely providing useful new facts or analysis.

I see this on social media a lot. I see a lot more people parroting or sharing a juicy tidbit that they seem to think carries a point (the point is not always clear and the facts are sometimes just wrong), but I rarely see someone address and issue with humility, reason or an admission of uncertainty.

Cartoonist Scott Adams noticed it in his social media interactions, too. He attributes some of this to the complexity of the world we live in and the issues we deal with; human beings are not very good and understating complexity. In addition, most people aren’t trained to think productively to produce reasonable solutions. As he put it in his book Loserthink, “Despite evidence to the contrary, we all use our brains. But most of us have never learned to think effectively.”

Loserthink is Adams’ term for unproductive, ineffective ways of thinking. He generously thinks that people are not stupid, they are just using unhelpful, unfruitful patterns of thinking.  You will get nowhere trying to shame people for stupidity, but you might get somewhere if you engage people in seeing how ridiculous is loserthink, and how it produces divisions that generally don’t benefit us (though it might benefit some).

Most of the book is devoted to identifying common types of loserthink an how to think more productively. He draws on ways of thinking from various professions and disciplines in which people are trained in thinking and problem solving: psychologists, artists, historians, engineers, leaders, entrepreneurs and economists.

Adams expresses some opinions about political and social issues that are likely to be controversial to some. Rather than take as evidence that you are right or that Adams is a dunce, take it as challenge to think things through for yourself. Test yourself to see if you might be engaging in loserthink. It might not change your mind, but it is likely to make you more modest about your certainty in some area, more confident in the workability of your solutions in others and generally more persuasive because you have check yourself for loserthink and you can gently help other address theirs.

Scott Adams also wrote

How to Fail at Almost Anything and Still Win Big

If you’re interested in this book, you may also be interested in

Bored and Brilliant by Manoush Zomorodi

The Checklist Manifesto by Atul Gawande

Choosing Civility by P. M. Forni

Freakonomics by Steven D. Levitt & Stephen J. Dubner

Histories and Fallacies by Carl R. Trueman

How Not to Be Wrong by Jordan Ellenberg

Range by David Epstein

Six Easy Pieces by Richard Feynman

The Thinking Life by P. M. Forni

Adams, Scott. Loserthink: How Untrained Brains are Ruining America. New York: Portfolio/Penguin, 2019.

Sunday, March 13, 2016

350 Books Reviewed on Keenan's Book Reviews

I’ve posted reviews of 350 books on this blog. It’s hard to believe.  Here are links to the 50 most recent posts. Further down are links to more reviews.

First Time Reviews











Additional and Expanded Reviews


Continuation of list of 350 books reviewed

Friday, May 15, 2020

Stat-Spotting by Joel Best


We are confronted with statistics in the news wherever we turn: television, radio, newspapers, magazines and the internet. It can be hard to sort out what meaning to make of the numbers, especially when there are competing statistics or interpretations.

Sociology professor Joel Best provides advice on recognizing suspicious statistics in Stat-Spotting. This is by no means a technical or mathematical guide to statistics. It is aimed squarely at the layman who is confronted by statistics in the news and from the mouths of politicians or experts.

A good place to start is with a bit of advice that Best puts toward the end of the book (this isn’t inconvenient; it is a short book). If a number seems shocking, unbelievable or far outside of what your own experience might lead you to expect, it is probably worth digging into it some more.

Not every bad statistic is the result of bad faith. By the time a statistic reaches the public, it has been through several hands. It starts with some research, which may be undertaking by a fairly neutral party or by an advocate. In either case, they have a motivation to get attention for their work. Someone has to bring a study to the attention of the media, and they may add a layer of interpretation on the statistics. Finally, reporters, editors and producers are looking for stories that are sufficiently interesting or important to draw an audience.

This is a process that can introduce mistakes, even unintentionally, and bring sensational statistics to the fore. Many of these people don’t know any more about research methods or statistical analysis that you. The math and logic of statistics, especially when it relates to probability, can be counterintuitive, and even professional researchers sometimes don’t have a solid grasp on it. Of course, some of these people are producing statistics with the intent of supporting a particular point of view.

Best points out 32 ways in which the statistics you see may have a problem. These are easy to grasp and don’t involve much if any math. He presents them in simple terms, and in each case provides an example from the news.

There are a lot of demands for our attention and action, and statistics are often cited as part of these appeals. It is helpful to approach these numbers with some skepticism. Stat-Spotting provides accessible tools for testing the reasonableness of the statistics we come across day to day.

If you’re interested in this book, you may also be interested in

Best, Joel. Stat-Spotting: A Field Guide to Identifying Dubious Statistics. Berkeley, CA: University of California Press, 2008.

Saturday, April 6, 2019

Naked Statistics by Charles Wheelan


Statistics provides of us with a power set of tools for describing things in our world and making inferences about them. They can also rely on math and logic that seems counterintuitive and they are subject to other pitfalls. Economist Charles Wheelan provides and accessible introduction into how we can use, misuse and abuse statistics in Naked Statistics.

Data is everywhere. In my life time, the falling prices and increased interconnectivity of computers have massively increased the collection of data. It can be overwhelming. At the same time, my experience as an engineer and government employee have left me frustrated with lack of data on some issue and wonder what inferences I might draw and how much I can rely on them.  Statistics provides us tools for dealing with these issues.

For instance, statistics provides us a way to summarize lots of data with a simple number such as an average (many people are familiar with sports statistics that summarize a performance of a play or team over a game, season or even a whole career). Statistics can help us find trends and estimate how much various factors may be contributing toward those trends. Even in the case where there is little data, statistics can help us evaluate the reliability of your conclusions (statistics can’t prove something definitively, but it can quantify how likely you are to be wrong).

“Statistics cannot prove anything with certainty.”-Charles Wheelan, Naked Statistics

Though he doesn’t delve too deeply into the mathematics of statistics, he shows that the math is often the easy part. Getting good data, designing experiments, constructing reasonable hypotheses, and avoiding bias present many stumbling blocks that can turn statistics into nonsense.

Not only that, people can take advantage of the weaknesses of statistics to provide persuasive support for wrong conclusions. Not everyone throwing around statistics intends to deceive, but a few do. A few just make mistakes, too. Wheelan describes many of the common mistakes people make while using statistics. This can help people new (or not new to statistics) avoid them. Possibly more important, it can help users of statistics recognize possible problems in how the statistics they use are developed or interpreted.

“Statistics cannot be any smarter than the people who use them.”-Charles Wheelan, Naked Statistics

This is not a statistics textbook. Wheelan does not delve into the details, but he does provide intuitive explanations of the concepts and simple examples. A student of statistics might find this book helpful in getting over some of the conceptual hurdles that may get in the way of understanding the rest of the material.

If you’re interested in this book, you may also be interested in

Wheelan, Charles. Naked Statistics: Stripping the Dread from Data. New York: W. W. Norton & Company, 2013.

Sunday, February 25, 2018

The Numerati by Stephen Baker

Hari Seldon used mathematics to study psychology and society. He developed the science of psychohistory, which he would use to predict future social, economic and political trends. This was utter science fiction when I read Foundation in high school, and doubly so in the 1940s when Isaac Asimov was writing and publishing the stories that would eventually become the novel. (By the way, psychohistory now refers to the application of methods from psychoanalysis to the study of history and social sciences.)

We’ve come a long way. Computers are much more powerful and many of us carry a networked computer around in our pockets much of the day. The computers record a lot of information about us, especially how we use them, and are crunching the numbers so people can anticipate our wants and influence our behaviors.

Stephen Baker gives us a glimpse into that world in his book The Numerati. “Numerati” is Baker’s term for the mathematicians, computer scientists and other math-literate scientists and professionals who are trying to use numbers and equations to describe and predict human behavior.

This type of analysis has applications in many areas. As you might expect, stores, marketers and advertisers are using it to try to sell us stuff. Not only are they trying to persuade us, they are segmenting the market to try to get the highest prices they can for their products from each buyer (and spend less time dealing with die-hard bargain shoppers).

Similarly, politicians are using this type of analysis to reach swing voters. Companies are trying to get the most out of workers.  Health insurance companies are seeking to minimize exposures to risk. Law enforcement is getting all the information it can lay hands on to try to find the terrorist lurking in our midst (finding a needle in a haystack may be easier).

That sounds sinister, and Baker has reservations about the benefits of us sharing so much information, but there are opportunities for those of us who are not numerati, or can’t afford a staff of mathematicians to do our bidding. The numbers that show which workers are most productive could be turned around to help us show our value and potential win a raise or promotion. The numbers that show minute changes in our behavior might help us diagnose and treat diseases earlier and less expensively, or help us live more fully with chronic diseases. They might even match us with a soul mate.

Though science and technology have advanced in the decade since this book was published, the data sciences Baker described are still new. Some of the things we see being done with computers on television or film are still new concepts that don’t work nearly as quickly or accurately as depicted. However, people are working every day to make these technologies better.

If you’re interested in this book, you may also be interested in


Baker, Stephen. The Numerati. Boston: Houghton Mifflin, 2008.