Showing posts with label statistics. Show all posts
Showing posts with label statistics. Show all posts

October 20 - World Statistics Day

Posted October 20, 2020

(Celebrated every five years)

This United Nations day - which is only celebrated every five years - this year has the theme "Connecting the World with Data We Can Trust."

It's only the third World Statistics Day (the first was in 2010). In 2015 the theme was "Better data, better lives." 


I like the intent here. We can only make good decisions if we consider facts and evidence - in other words, data. We can only learn from the past by consulting data.

And, crucially, we can only reach a consensus if we share the same set of "facts." Obviously, carefully collected evidence-based data is factual - but there are "statistics" and "data" presented as if they were facts that are actually misinformation or disinformation. People making up lies that work in their favor, or people fudging experimental results for the sake of pleasing whoever is funding the research, or people tossing out bunches of data points that don't fit with the preferred narrative - the results of these kinds of shenanigans - even if they are dressed up with the language of statistics - are not factual. There is no such thing as "alternative facts." 
 


It is good for everyone if we develop trust for organizations and journalists that deal with real data and true information. I'm not sure how to get there - but we need "data we can trust"!

The Internet Society has an important motto: "The data-driven world doesn't run on data; it runs on trust."





April 24 – Happy Birthday, John Graunt

Posted on April 24, 2014

At the time that Graunt lived,
the European fashion for
hats was the capotain, seen
here. Both men and women
wore capotain hats.
Today's birthday boy made and sold hats—in other words, he was a haberdasher.

I am not writing about him because of his haberdashery, though. As a matter of fact, if ALL he ever did was make and sell hats, I never would have heard of John Graunt. He did, after all, live about 400 years ago!

No, the reason I am writing about Graunt—the reason he is famous—is that he was one of the world's first demographers.

Demography is the study of human populations through statistics, such as numbers of births, deaths, and marriages, amount of income, and so on. Graunt, born on this date in 1620, was able to use more than a century's worth of records of baptisms and deaths, kept in English churches, to answer questions about death rates. He discovered that death rates differed for men and women, and that death rates differed for city and rural populations.

Because he looked at the causes of death, Graunt is also considered one of the first experts on epidemiology (the study of the spread of diseases). He even tried to help England's king create a system of warning of the onset and spread of bubonic plague, using statistics; even though the system never was completed, Graunt's efforts did create the first statistically based estimation of the population of London.

Graunt presented his demographic studies to the Royal Society. Apparently many members of the Royal Society wanted nothing to do with Graunt and did not want a mere haberdasher to be elected to their august organization. But Charles II, King of England, brought Graunt into the society despite their reluctance.

Unfortunately, Graunt lived at a time when religious differences were tearing apart the nation; Graunt had converted to Catholicism shortly before the Great Fire of London, and when the fire was blamed on Catholics, Graunt lost his job. He ended his life very poor, suffering from some of the diseases he may have studied.

Explore demography

In the almost four centuries since Graunt, improvements in medicine and hygiene have improved our lives and health. However, all is not equal all over the world. Check out this graph of life expectancy (above), which shows that women tend to outlive men and the not-at-all-surprising fact that people in richer nations tend to outlive people in poorer nations. The Wikipedia article that provides the graph also gives the rankings and the hard numbers. Try to guess where your own nation will appear in the chart (#1? #7?) before you check it out. 

ChartsBin has a map that shows the daily calorie intake per capita (per person), all over the world. 

Demographic studies often tell us sad truths. I looked at this bar graph (below) showing the income gap by race in my own nation, the United States. I hoped that the fact that the numbers were from ten years ago would mean that the gap had shrunk...

...but then I spotted this graph (below) of the income gap by race and gender, and I realized that the gap has probably grown. This graph shows growth in the income gap along racial and gender lines for the last forty years of the last fifty years, and I fear that the trend has continued! Can you discover whether or not the gap has widened even more from 2004 to 2014?
The dates along the bottom of the graph range from '68 (1968) to '08 (2008),
with each number being two years beyond the last.

The average annual income is shown by the horizontal bars, with $10K
being the bottommost line, then $20K, $30K, $40K, $50K, and the
top line being $60K.
In other words, each horizontal line is separated from the one
below by ten thousand dollars.


Also on this date:


First Day of Summer in Iceland









Plan ahead:

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September 8, 2010


Dr. John Snow uses NUMB3RS to stop an epidemic!

To me, the history of the 1854 cholera epidemic in London reads a bit like a NUMB3RS episode (a CBS television show that ran for six seasons, starring a mathematician who used his math to help the FBI solve cases).

Most people back in the mid-1800s thought that illness was caused by breathing “bad air” or miasma—breathing poisonous vapors of some sort. However, Snow was skeptical of that theory. When there was a deadly outbreak of cholera in London, he talked to residents and created a map showing the location of the cases. Through these means he was able to trace the outbreak to the public water pump on Broad Street in Soho.

Snow was most convinced that the pump was to blame when he discovered that people who lived nearby who did NOT use water from that pump also did not come down with cholera.

Snow examined a sample of the water through a microscope, and ran some chemical tests as well, and he was not able to conclusively prove its danger. However, he still used statistics and his map to convince the local council to disable the water pump by removing its handle on this date in 1854.

And the outbreak stopped.

Later, it was discovered that this public well had been dug only three feet from an old cesspit, and it was being polluted by sewage. Snow was able to use statistics to show that a waterworks company was using water from sewage-polluted portions of the Thames River for use in homes—and those homes suffered from more cases of cholera than other homes. Because of Snow's work, our understanding of disease prevention and public health took a giant leap.

Yeah for numbers!

Learn more...

  • Here is a virtual tour of a modern water treatment plant. 

  • Here is a game in which you can be an epidemiologist (one who studies disease and epidemics). Look for the words "Role-Playing Games" at the left side, and click "GO." By the way, the sound didn't work for me...but I didn't need it, either... 

  • Part of numbers and statistics is probability. Try using this dice-roll simulation. Roll the dice 5 time, then 50, 500, and 5000. How does the number of rolls affect the results?