I saw in the news recently that Hewlett-Packard (HP) has re-issued the first hand-held scientific calculator introduced in 1972 for what was then the huge sum of $395 – half a month’s salary for an engineer just graduating around that time. The price for their new retro calculator is $60, which would only set back about two hours’ earnings of an engineer nowadays. The HP calculator that I first used at General Mills Chemical Inc. (GMCI) was shared by our entire group of process-development engineers. It was bolted to a table! I never took to HP’s highly-touted reverse polish notation (RPN), so unless a really precise calculation would be of value, I stuck with my slide rule or pencil and paper.

Our marketing director saw the photo of me at my GMCI desk and guessed that it dated back to 1971. She and her staff came up with a fun, retro theme for announcing our newest versions of Design-Ease® and Design-Expert® design-of-experiment (DOE) software – V7.1. I really felt old having to tell her that the picture was taken in the late ‘70’s. In 1971 I was a senior in high school and pocket calculators were yet to be invented. The personal calculator pictured, from Texas Instruments I believe, did not do logarithms, so I continued to carry a slide rule into the ‘80’s for accomplishing this function.

When R. A. Fisher invented DOE in the 1920’s at Rothamsted Experimental (Agricultural) Station in England, computations were done by ‘calculators’ – a room-full of mathematically adept people (mainly female). Rothamsted did not get a computer until 1954, just after this photo of Fisher was taken with his mechanical calculator.

“Fisher never concerned himself much with electronic computers – I remember him referring to them as ‘meccano arithmetic’…”
— F. Yates, The First Fisher Memorial Lecture on “Computers, The Second Revolution in Statistics,” March 23, 1966, British Museum, London (published in Biometrics, Vol. 22, No. 2 (Jun., 1966), pp. 233-251.)

The invention of response surface methods (RSM) by Fisher’s successor (and son-in-law) George Box made computers more of a necessity. Today no one would consider doing DOE without one.

So, it seems that calculators are going the way of slide rules and dinosaurs. I quit using mine many years ago – not counting the handy accessory provided by Microsoft. However, calculator hardware is still hanging on as evidenced the American version of the television show The Office (inspired by the same-named British show): See in this educational article a photo of Dwight’s calculator encased in gelatin by his colleague Jim. In a later episode Jim tries this again on a new colleague, Andy – who rivals Dwight for nerdiness, but the prank backfires by creating a huge blow-up in The Office. (If you are an office worker, you have to enjoy this over-the-top stuff!) Evidently calculators are still very important for some folks.

(Photo by my nephew Ross Nelson taken in the immediate aftermath of the I35 bridge collapse)

“All happy families are alike; each unhappy family is unhappy in its own way.” So begins Tolstoy’s classic novel Anna Karenina. According to Steven M. Shugan of the Warrington College of Business at University of Florida, it can be inferred from this statement that the most revealing factors for success might exhibit negligible variation among survivors in the struggle for dominance by enterprises at all levels, from businesses to entire civilizations. In honor to Tolstoy’s memorable introduction, he introduces the statistical term “TAK bias” in his editorial titled “The Anna Karenina Bias: Which Variables to Observe?” published in Vol. 26, No. 2, March-April 2007 of Marketing Science (underlines by me). (The author credits Pulitzer Prize winner Jared Diamond for introducing the Anna Karenina principle.) Shugan fears that many studies of what constitutes success are based on passive data collection that excludes nonsurvivors.

Ideally, researchers can take an active role in setting factor levels that produce a range of responses from failure to success. This is feasible for our clientele — mainly industrial experimenters working on process and product development or manufacturing improvement. For obvious reasons, it does no good to only produce perfect results. To put it plainly, one learns from his or her mistakes.

In our business of software development, one hopes that only good code will be written, but if it fails, ideally it will fail fast as pointed out in an article by Jim Shore published by IEEE SOFTWARE in September/October 2004 .

Unhappily, we need not be concerned about TAK bias in the case of a catastrophic failure such as the collapse of the I35 bridge entering downtown Minneapolis. Returning from Sunday’s exhilarating Minnesota Twins game, featuring a team-record 17 strikeouts by their ace pitcher Santana, my bubble of happiness burst when crossing the Mississippi on the Old Stone Bridge just up-river from the carnage. I have no doubt that the next bridge will be built for the ages, but I am less sanguine about other structures that still stand in spite of their decrepitude.

Thursday morning seemed surreal on my dawn commute to the shaken city of Minneapolis the morning after their downtown’s entryway collapsed catastrophically. Drivers darted this this way and that, seeking alternate routes. As I walked in from the parking lot, a helicopter hovered directly overhead our building taking pictures of the I35W bridge remains. Cartoonist Marshall Ramsey captured all of our anxieties nowadays by picturing a span held up by question marks. I just hold my breath and speed up until crossing over and then breathe a sigh of relief!

The really important question is the cause of this precipitous breakdown in this vital structure. CNN’s widely seen video seemingly pinned the south end as the point of failure, but the northern end of I-35W bridge is now focus of probe. I heard one expert on the engineering of bridges say we should not be overly concerned about another bridge failure anytime soon because this one is an “anomaly”!

When the consequences are trivial, it is easy to dismiss events of such extremely low probability. However, in an extremely high-impact case like this, we want to know the risks of it happening again – assuming no intervention will be accomplished any time soon. This weekend I saw the August issue of The American Statistician magazine, which features reviews of a book titled The Black Swan: Impact of the Highly Improbable by Nassim Nicholas Taleb. According to Taleb’s home page named after his first book Fooled by Randomness /, Taleb’s goal in life is “…teasing people who take themselves & the quality of their knowledge too seriously & those who don’t have the guts to sometimes say: ‘I don’t know’….”

Taleb borrowed the black swan concept from philosopher Karl Popper. Before these birds were found prevalent in Australia (beautifully detailed by Black Swan wines ), they were thought to be extremely rare by the Western world. Taleb says that it may be emotionally satisfying, but we accomplish little by trying to explain catastrophes such as the 9/11 attack, and fool ourselves by quantifying their risk of re-occurrence. (I wonder if this serves as an example — the five threat levels predicted by the US department of Homeland Security, Low = Green; Guarded = Blue; Elevated = Yellow (current level); High = Orange; Severe = Red.)

Taleb obviously gets a kick out of tweaking the noses of pontificators purporting predictive powers on the next improbable high-impact event. However, I am studying with great interest all ongoing reports from the investigation of the I35 bridge collapse just down the road from my Stat-Ease office, not only for it being so proximate, but also for my peace of mind in having to constantly cross other spans over our region’s rivers and highways. I look forward to the day when our bridge gets rebuilt and perhaps we can again enjoy swans of any sort swimming along the banks of the Mississippi in downtown Minneapolis.