from the world's big
Is all the truth we need in the data?
Although it seems savvy to defer to “the data,” the devil is in the mixed details. For example, humans on average have one testicle and one ovary.
Is all the truth we need found in the numbers? Can the stats always chart a better course? Although it seems savvy to defer to “the data,” the devil is in the details.
1. “Eliminating all police bias,” calculates Sendhil Mullainathan (The New York Times) wouldn’t materially reduce police killings of African-Americans. Nationally, African-American = 28.9 percent of arrestees vs. 31.8 percent of police-shooting victims. If racism “were a big factor,” Mullainathan would expect “a larger gap.”
2. That’s a common stats weakness. The national data hide huge variations — 70 police forces arrest African-Americans at rates 10 times higher than other groups. In such places, the national stats are irrelevant. Stats help when they’re representative of the particulars. Otherwise the satanically slippery stats can mislead even experts (e.g., Mullainathan, and responses here and there miss the main relevance issue).
3. Here’s a medical example — Stephen J. Gould’s “The Median Isn’t The Message.” He knew his cancer’s median mortality of eight months didn’t necessarily mean he’d “probably be dead in eight months." His particulars weren’t well-represented by the stats. He lived another 20 years.
4. More funnily... mixed types can mangle data — humans on average have one testicle and one ovary.
6. “Evidence-based” medicine’s Randomized Clinical Trials (RCT) can’t “even in principle” always deliver. RCTs “return average effects.” Great for sufficiently homogenous populations, but riskier with subpopulations of differing types/responses. Larger samples with inhomogeneous types can weaken relevance (Mullainathan above).
7. Human behavior varies more than human physiology, suggesting RCT issues in social sciences (e.g., economies have inhomogeneous behavioral mechanisms/processes).
8. Statistics, crucial to science, are also perhaps its “tragic ... flaw.” Relying on the “statistical significance” recipe doesn’t ensure real-world importance (and not everything is bell-curved). Bad stats and other data biases contribute to ills in many fields (e.g., neuroscience, psychology, economics). Heaven help journalists (or these earthier volunteers).
9. Even plain, un-statistical numbers can lose context and real-world sense logic, causing “spreadsheet madness” — Larry Summers knows experts who’d argue electricity is “4 percent of the economy,” so losing much of it couldn’t hurt. Dollars especially can seem too easily comparable — risking “the spice error,” small factors ≠ unimportant.
10. Tools must match the domain. Stats excel in physics, where behaviors are stable (nothing in physics chooses). But people aren’t biological billiard balls. Our games are complicated by our choosing and changing how we choose.
11. Sports are simpler than economics and life. And we know stats in sports aren’t a sure bet. Sports and life are too polycausal (see oli- vs. poly-causal sciences). High “causal density” can subvert the utility of stats.
12. Turning the world into numbers is tricky. Never forget what the numbers really refer to.
Numbers have no monopoly on precision or truth. We’ll always need non-numerical logic (the quality of quantitative reasoning rests on good qualitative distinctions).
Many of life’s patterns remain beyond “the numbers.”
Illustration by Julia Suits, The New Yorker cartoonist & author of The Extraordinary Catalog of Peculiar Inventions
Join multiple Tony and Emmy Award-winning actress Judith Light live on Big Think at 2 pm ET on Monday.
The team caught a glimpse of a process that takes 18,000,000,000,000,000,000,000 years.
- In Italy, a team of scientists is using a highly sophisticated detector to hunt for dark matter.
- The team observed an ultra-rare particle interaction that reveals the half-life of a xenon-124 atom to be 18 sextillion years.
- The half-life of a process is how long it takes for half of the radioactive nuclei present in a sample to decay.
What we know about black holes is both fascinating and scary.
- When it comes to black holes, science simultaneously knows so much and so little, which is why they are so fascinating. Focusing on what we do know, this group of astronomers, educators, and physicists share some of the most incredible facts about the powerful and mysterious objects.
- A black hole is so massive that light (and anything else it swallows) can't escape, says Bill Nye. You can't see a black hole, theoretical physicists Michio Kaku and Christophe Galfard explain, because it is too dark. What you can see, however, is the distortion of light around it caused by its extreme gravity.
- Explaining one unsettling concept from astrophysics called spaghettification, astronomer Michelle Thaller says that "If you got close to a black hole there would be tides over your body that small that would rip you apart into basically a strand of spaghetti that would fall down the black hole."
A new study looks at what would happen to human language on a long journey to other star systems.
- A new study proposes that language could change dramatically on long space voyages.
- Spacefaring people might lose the ability to understand the people of Earth.
- This scenario is of particular concern for potential "generation ships".