Tom Friedman's Law of Statistics refutes Chapter 1

Reading this completely incoherent, frustratingly unfathomable column by Tom Friedman, the star columnist at the New York Times, I wanted to pull my hair out. From first word to last, he confuses averages and extremes -- the stuff in my Chapter 1, which is the very first concept in statistics.

Friedman has discovered a new law of statistics: to understand averages, look at extremes.

Starting from the end. He claims that the average American should learn from the average immigrant parents who value education more. His evidence: half of the 32 Rhodes scholar winners have foreign-sounding names. Where to begin?

1. Rhodes scholars are outliers. The existence of outliers does not imply that the median immigrant kid has better educational outcomes. It appears that Friedman has never heard of the "achievement gap", that is, the average test score of most minority groups are far below that of white students. Any teacher can tell you trying to raise the average performance in a class and trying to nurture the top student requires completely different approaches, probably mutually exclusive. Setting policies for everyone based on outliers is not very smart.

2. He equates Rhodes scholars with "America's top college grads". Maybe recognized by some as such but certainly not by all.

3. If he knows any immigrant kids, he'll learn that it makes a big difference whether you are first generation or latter generations, and looking at names does not give you a hint of this key distinction.

Friedman starts the piece trapped in an impossible unpainted corner. Using the story of a girl who texts 27,000 times a month on average, he claims that today's unemployment problem is partly a function of kids not going to college, and they don't go to college because they waste their time texting. Where to begin?

4. He goes on to say, and I quote: "I don’t want to pick on Miller [the girl]. I highlight her words only because they’re integral to a much larger point..." Miller is clearly an outlier (see this recent Nielsen data for evidence). How an extreme case can be "integral" to making a "much larger" point, presumably about the average American is beyond me.  We are not even complaining about a sample size of 1 but a sample size of 1 extreme case. Beyond frustrating.

5. The unemployment report that tells us only half of B.A. graduates found jobs requiring a college degree apparently has not yet reached his desk, after over two years. (See for instance this blog post by two seniors.) Among 18-24 year olds, the unemployment rate is 25% (!!!), not counting the underemployed and "marginally attached" and "discouraged".

6. Texting is not the only distraction, and is probably not the most important reason why some kids are not going to college, or fail to graduate.

7. In Friedman's world view (shared and pushed by a bunch of economists who call this "structural unemployment"), it is not a problem that we have eliminated most jobs suitable for people with high school diplomas. When these people can't find jobs, it is their own fault, and their parents' fault. I am not sure how his algebra works: he mentions the case of the micro-chip replacing his receptionist; you know what, one micro-chip will replace an entire team of receptionists - that's the nature of technology replacing labor; and if, as Friedman seems to agree, the "low-end" (read: labor intensive) jobs producing the technology will be exported due to globalization, I am not understanding how the numbers add up - don't we end up with fewer jobs? There is a shift to higher-end jobs but aren't there fewer total jobs?

Now, let's venture into the middle of the column. Friedman claims that Americans have to "step up their game" because of competition from foreign students. How does he know that foreign students are providing tough competition? Look at "two of our most elite colleges" (those in his world are Harvard and Yale); look at foreigners applying to "Ivy League schools". Say what? He thinks these extreme outliers will tell us something about "every school". So there it is again, Tom's Friedman Law of Statistics: to understand the average, look at the outliers.

What Friedman's column proves is that having gone to college and grad school (Brandeis and Oxford) is no guarantee that you can make a cogent argument based on evidence.

 

Comments

[Bronx Teacher]

The last two columns that Friedman has written have shown that he does not get it, or is just a shill. Unfortunately I think he has become a shill and I have lost a great deal of respect for him.

[twitter.com/bob_calder]

Tom needs to go back and re-read The Lexus and the Olive Tree. The outpouring of conservative FUD hasn't changed the rest of the world.

To quote School Finance 101, Freidman's statistics are like those of charter school proponents in that the "best charter schools outperform the average public schools.'

An indictment of American character as the basis for criticism is at best, silly.

[Manoel Galdino]

I liked your text and usually like uyour blog.

However, I do think you are wrong in point number 7. New tech will not reduce employment in the long run, and maybe not even in the short run.

The increase in productivity will boost the economy, creating more employments in other sectors. Besides that, new technology increase output per worker.

For example, let's say we live in a one-sector economy at time t0. We produce y0 per worker. Total output is L*y0 (L is the total number of workers). Technology, here is equal to 1. So, our GDP = L*y0. Now, suppose we have a new technology at time t1 that enhance productivity per worker. Now we poduce 1.1y0 per worker. If the economy doesn't grow, we will have unemployment. The total employment will be L/1.1, and a few people are unemployed (10%).
Now, if the GDP grows by the same amount as productivity, we will have zero unemployment!

best regards,
Manoel

of before, we'll have: Ly0 =

[Kaiser]

Manoel: thanks for the comment. I stated Point 7 as a question in the hope that some readers like yourself would help explain the thinking. Of your explanation, I understand that if we assume increasing productivity in one sector "creates jobs in other sectors", then overall employment will increase. I have difficulty grasping how this assumption is actualized.

In Friedman's example, the function of "receptionist" is made more productive with less labor by the use of computers and it generates more jobs in the high-tech sector; however, as per Friedman's argument, many of the new jobs are outsourced to other countries (at least the manufacturing jobs and increasingly also design jobs) so it's not clear to me that net jobs in the U.S. must increase.

As I think about it more, in the short run, one can use an argument of market inefficiency to claim that there will be more net jobs. What I mean is stickiness: it seems to me that many jobs take time to eliminate whether it is due to unions, contracts or decency; and computer systems and technologies are even harder to decommission. Of the former, I can point to the baffling longevity of the yellow-pages business; of the latter, the fact that Bank of America has not integrated its California systems with the East Coast systems more than five years after the merger is one of many examples. Thus, I can make an argument that there could be a short-term net increase in jobs but that wouldn't be due to market efficiency but rather the lack of it.

Any further thoughts?

[Hasan Diwan]

@Kaiser Friedman's thinking requires a tacit assumption that the nation-state is no longer relevant. If you disregard the notion that "this" piece of land is "the United States" and "that" piece of land is "India" and think of both pieces of land as "planet Earth", his argument that the function of a "receptionist" being automated generating more high-tech jobs does hold true.

[Cristal Mcmeans]

I agree with Manoel. New technology doesn't necessarily mean that there's no more work for the good old man-powered production. Even if this is the case, I don't see why anyone would replace an employee with new technology; since unlike microchips and computers, human employees have no limits to their potential. Even someone who doesn't have a college diploma can perform well at work with the right training and good seminars. Like for example, TPM presentations can increase a machine/tool operator's capabilities significantly, being briefed with the tool/machine's basic troubleshooting and proper usage! Or increase your employee's production via a SMED presentation or seminar! I really think that no matter how much you upgrade your new tech, it can never replace a working, LEARNING human.