(Roughly) Daily

Posts Tagged ‘infographics

“When the graphs were finished, the relations were obvious at once”*…

We can only understand what we can “see”…

… this long-forgotten, hand-drawn infographic from the 1840s… known as a “life table,” was created by William Farr, a doctor and statistician who, for most of the Victorian era, oversaw the collection of public health statistics in England and Wales… it’s a triptych documenting the death rates by age in three key population groups: metropolitan London, industrial Liverpool, and rural Surrey.

With these visualizations, Farr was making a definitive contribution to an urgent debate from the period: were these new industrial cities causing people to die at a higher rate? In some ways, with hindsight, you can think of this as one of the most crucial questions for the entire world at that moment. The Victorians didn’t realize it at the time, but the globe was about to go from less than five percent of its population living in cities to more than fifty percent in just about a century and a half. If these new cities were going to be killing machines, we probably needed to figure that out.

It’s hard to imagine just how confusing it was to live through the transition to industrial urbanism as it was happening for the first time. Nobody really had a full handle on the magnitude of the shift and its vast unintended consequences. This was particularly true of public health. There was an intuitive feeling that people were dying at higher rates than they had in the countryside, but it was very hard even for the experts to determine the magnitude of the threat. Everyone was living under the spell of anecdote and availability bias. Seeing the situation from the birds-eye view of public health data was almost impossible…

The images Farr created told a terrifying and unequivocal story: density kills. In Surrey, the increase of mortality after birth is a gentle slope upward, a dune rising out of the waterline. The spike in Liverpool, by comparison, looks more like the cliffs of Dover. That steep ascent condensed thousands of individual tragedies into one vivid and scandalous image: in industrial Liverpool, more than half of all children born were dead before their fifteenth birthday.

The mean age of death was just as shocking: the countryfolk were enjoying life expectancies close to fifty, likely making them some of the longest-lived people on the planet in 1840. The national average was forty-one. London was thirty-five. But Liverpool—a city that had undergone staggering explosions in population density, thanks to industrialization—was the true shocker. The average Liverpudlian died at the age of twenty-five, one of the lowest life expectancies ever recorded in that large a human population.

There’s a natural inclination to think about innovation in human health as a procession of material objects: vaccines, antibiotics, pacemakers. But Farr’s life tables are a reminder that new ways of perceiving the problems we face, new ways of seeing the underlying data, are the foundations on which we build those other, more tangible interventions. Today cities reliably see life expectancies higher than rural areas—a development that would have seemed miraculous to William Farr, tabulating the data in the early 1840s. In a real sense, Farr laid the groundwork for that historic reversal: you couldn’t start to tackle the problem of how to make industrial cities safer until you had first determined that the threat was real.

Why the most important health innovations sometimes come from new ways of seeing: “The Obscure Hand-Drawn Infographic That Changed The Way We Think About Cities,” from Steven Johnson (@stevenbjohnson). More in his book, Extra Life, and in episode 3 of the PBS series based on it.

* J. C. R. Licklider

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As we investigate infographics, we might send carefully calculated birthday greetings to Lewis Fry Richardson; he was born on this date in 1881.  A mathematician, physicist, and psychologist, he is best remembered for pioneering the modern mathematical techniques of weather forecasting.  Richardson’s interest in weather led him to propose a scheme for forecasting using differential equations, the method used today, though when he published Weather Prediction by Numerical Process in 1922, suitably fast computing was unavailable.  Indeed, his proof-of-concept– a retrospective “forecast” of the weather on May 20, 1910– took three months to complete by hand. (in fairness, Richardson did the analysis in his free time while serving as an ambulance driver in World War I.)  With the advent of modern computing in the 1950’s, his ideas took hold.  Still the ENIAC (the first real modern computer) took 24 hours to compute a daily forecast.  But as computing got speedier, forecasting became more practical.

Richardson also yoked his forecasting techniques to his pacifist principles, developing a method of “predicting” war.  He is considered (with folks like Quincy Wright and Kenneth Boulding) a father of the scientific analysis of conflict.

And Richardson helped lay the foundations for other fields and innovations:  his work on coastlines and borders was influential on Mandelbrot’s development of fractal geometry; and his method for the detection of icebergs anticipated the development of sonar.

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“Your job as a scientist is to figure out how you’re fooling yourself”*…

Larger version here

And like scientists, so all of us…

Science has shown that we tend to make all sorts of mental mistakes, called “cognitive biases”, that can affect both our thinking and actions. These biases can lead to us extrapolating information from the wrong sources, seeking to confirm existing beliefs, or failing to remember events the way they actually happened!

To be sure, this is all part of being human—but such cognitive biases can also have a profound effect on our endeavors, investments, and life in general.

Humans have a tendency to think in particular ways that can lead to systematic deviations from making rational judgments.

These tendencies usually arise from:

• Information processing shortcuts

• The limited processing ability of the brain

• Emotional and moral motivations

• Distortions in storing and retrieving memories

• Social influence

Cognitive biases have been studied for decades by academics in the fields of cognitive science, social psychology, and behavioral economics, but they are especially relevant in today’s information-packed world. They influence the way we think and act, and such irrational mental shortcuts can lead to all kinds of problems in entrepreneurship, investing, or management.

Here are five examples of how these types of biases can affect people in the business world:

1. Familiarity Bias: An investor puts her money in “what she knows”, rather than seeking the obvious benefits from portfolio diversification. Just because a certain type of industry or security is familiar doesn’t make it the logical selection.

2. Self-Attribution Bias: An entrepreneur overly attributes his company’s success to himself, rather than other factors (team, luck, industry trends). When things go bad, he blames these external factors for derailing his progress.

3. Anchoring Bias: An employee in a salary negotiation is too dependent on the first number mentioned in the negotiations, rather than rationally examining a range of options.

4. Survivorship Bias: Entrepreneurship looks easy, because there are so many successful entrepreneurs out there. However, this is a cognitive bias: the successful entrepreneurs are the ones still around, while the millions who failed went and did other things.

5. Gambler’s Fallacy: A venture capitalist sees a portfolio company rise and rise in value after its IPO, far behind what he initially thought possible. Instead of holding on to a winner and rationally evaluating the possibility that appreciation could still continue, he dumps the stock to lock in the existing gains.

An aid to thinking about thinking: “Every Single Cognitive Bias in One Infographic.” From DesignHacks.co via Visual Capitalist.

And for a fascinating look of cognitive bias’ equally dangerous cousin, innumeracy, see here.

* Saul Perlmutter, astrophysicist, Nobel laureate

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As we cogitate, we might recall that it was on this date in 1859 that “The Carrington Event” began. Lasting two days, it was the largest solar storm on record: a large solar flare (a coronal mass ejection, or CME) that affected many of the (relatively few) electronics and telegraph lines on Earth.

A solar storm of this magnitude occurring today would cause widespread electrical disruptions, blackouts, and damage due to extended outages of the electrical grid. The solar storm of 2012 was of similar magnitude, but it passed Earth’s orbit without striking the planet, missing by nine days. See here for more detail on what such a storm might entail.

Sunspots of 1 September 1859, as sketched by R.C. Carrington. A and B mark the initial positions of an intensely bright event, which moved over the course of five minutes to C and D before disappearing.

“Earth is a small town with many neighborhoods in a very big universe”*…

… full of very large objects. From @nealagarwal, a scroll-able comparison of the size of the objects that surround us in in the universe: “Size of Space.”

(Listen to outer space here.)

For other nifty visualizations, visit his site and check out, e.g., “The Deep Sea.”

* Ron Garan

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As we internalize insignificance, we might send distantly-observed birthday greetings to Harlow Shapley; he was born on this date in 1885. An astronomer known as “the Modern Copernicus,” he did important work first at the Mt. Wilson Observatory, and then as head of the Harvard College Observatory. He boldly and correctly proclaimed that the globulars outline the Galaxy, and that the Galaxy is far larger than was generally believed and centered thousands of light years away in the direction of Sagittarius: he discovered of the center of our Galaxy, and of our position within it.

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Written by (Roughly) Daily

November 2, 2020 at 1:01 am

“There is a magic in graphs”*…

A New Chart of History
Joseph Priestley 1769, London
illustrates the succession of empires to give students a more global view of history across space and time. Vertical space indicates each empire’s significance, as assigned by Priestley. Click here for zoomable version

Data visualization leapt from its Enlightenment origins and into the minds of the general public in the 1760s. It cast more powerful spells throughout the following century. By 1900, modern science, technology, and social movements had all benefited from this new quantitative art. Its inventions include the timeline, bar chart, and thematic map. Together, these innovations changed how we understand the world and our place within it. Data visualization helped a new imagination emerge, wired to navigate a reality much bigger than any single person’s lived experience…

From the introduction to Stanford Library’s (more specifically, the David Rumsey Map Center‘s; @DavidRumseyMaps) glorious exhibition “Data Visualization and the Modern Imagination,” curated by R.J. Andrews (@infowetrust).

Visit the exhibition here.

* Henry D. Hubbard, in the preface to Graphic Presentation

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As we show and tell, we might recall that it was on this date in 1908 that Henry Winzeler founded the Ohio Art Company. Ohio Art began by offering metal picture frames, but soon settled into into two lines of business: toys (e.g., windmills and a climbing monkey) and custom metal lithography products for food container and specialty premium markets.

Those two themes merged in the very late 1950s, when Ohio Art acquired the rights to French electrician André CassagnesL’Écran Magique (The Magic Screen)– a drawing toy that allowed users to spin knobs to create line drawings, which could be erased by by turning the device upside down and shaking it. Ohio Art renamed it the Etch A Sketch… and it went on to sell over 100 million units and to earn a place in the National Toy Hall of Fame.

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Written by (Roughly) Daily

October 6, 2020 at 1:01 am

“Wherever you are right now, you’re just taking a break”*…

BTS

All seven members of boy band BTS have become multimillionaires after their label, Big Hit Entertainment, pulled off South Korea’s biggest stock market listing in three years. The K-pop label is issuing its shares at 135,000 won ($115) each, Big Hit said in a filing on Monday, raising 962.55 million won ($822 million) and valuing the company at 4.8 trillion won ($4.1 billion). That makes the deal South Korea’s largest stock offering since July 2017, according to data compiled by Dealogic…

CNN

K-Pop is huge, generating huge sales and cultural impact around the world. But what, readers of a certain age might ask, is K-Pop? And why are the groups so large? Our friends at The Pudding ride to the rescue:

Try typing “Why are K-pop groups…” into Google search and autocomplete offers several suggestions: “…so large,” “…so big” and “…so popular.” The rapid global growth of Korean music over the past decade has puzzled non-fans (and even experts), and it seems that the size of K-pop groups might be a mystery, too.

Traditionally, rock bands have as many members as there are instruments: a lead singer, two guitarists, and a drummer. Popular Western boy groups—like The Jackson Five, New Kids on the Block, Boyz II Men, Backstreet Boys, N*Sync, The Jonas Brothers, One Direction—and girl groups—like The Supremes, Destiny’s Child, TLC, The Spice Girls, and Little Mix—have ranged in size from 3-5 members. Compared to those numbers, K-pop groups with 7 or 9, or even 23 members (yes, a group that big exists) might seem alien, or downright excessive. And yet the average size of the top 10 selling K-pop groups of the last decade (like girl group TWICE, pictured above) is 9 members.

So, how did groups get that large? What about large groups is so appealing? And, what do the sizes of K-pop groups tell us about why K-pop is so popular?

To answer those questions, we tracked trends in group sizes and member roles over modern K-pop’s 30-year history, breaking the numbers down across the industry’s three generations of artists…

Elegant infographics explain: “Why are K-pop groups so big?

* BTS

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As we ponder popularity, we might recall that it was on this date in 1976, during Saturday Night Live‘s second season, that musical guest Joe Cocker performed his hit version of Traffic‘s “Feelin’ Alright.” In the event, the audience got not one Cocker, but two, as an identically-dressed John Belushi (already noted for his Cocker impression) came out with Joe for the full live performance. The two traded lines and successfully mirrored each other –a testament to both Cocker’s trademark stage presence and Belushi’s remarkable impersonation abilities. New York’s own jazz-funk heroes Stuff (hence the shirts in the video) backed them up.

Written by (Roughly) Daily

October 2, 2020 at 1:01 am