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Introduction to Statistical Reasoning. Excerpts from 1984, George Orwell (1903 – 1950)

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Introduction to Statistical Reasoning

Excerpts from 1984, George Orwell (1903 – 1950)

“The fabulous statistics continued to pour out of the telescreen. As compared with last year there was more food, more clothes, more houses, more furniture, more cooking pots, more fuel, more ships, more helicopters, more books, more babies – more of everything except disease, crime, and insanity……”

“Statistics were just as much a fantasy in their original version as in their rectified version.

A great deal of the time you were expected to make them up out of your head. For example, the Ministry of Plenty’s forecast had estimated the output of boots for the quarter at a hundred and forty-five million pairs. ”

"Lies, damned lies, and statistics“ – Popularized by Mark Twain

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Introduction to Statistical Reasoning

Malcolm Gladwell, author of Blink, recently said that if he were trying to break into journalism today, he would start by getting a master’s degree in statistical reasoning.

The Harvard psychologist Steven Pinker, who reviews Gladwell’s “What the Dog Saw” on this week’s cover, might second this advice.

Asked via e-mail what is the most important scientific concept that lay people fail to understand, he responded:

“Statistical reasoning. A difficulty in grasping probability underlies fallacies from medical quackery and stock-market scams to misinterpreting sex differences and the theory of evolution.” — New York Times, November 13, 2009

“One thing the modern computer age has given everyone is data. Lots and lots of data. There is a large leap, however, between having data and learning from it. Students need to know the potential of number-crunching, as well as its limitations.

All college students are well advised to take one or more courses in statistics, at least until high schools update what they teach.”

- N. GREGORY MANKIW, Professor of Economics at Harvard - New York Times, September 4, 2010 – A Course Load for the Game of Life

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Introduction to Statistical Reasoning

Statistics and Statistical Reasoning

  • Statistics,  the science of collecting, analyzing, and interpreting data.
  • What Is “Data”?
  • Numbers.
  • Pieces of information that have a meaning attached.
  • Statistical Reasoning is the way people reason with statistics and make sense of statistical
  • information.
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Introduction to Statistical Reasoning

Uses of Statistics

  • Imagine baseball without batting averages, number of bases stolen, runs scored, games won and lost, and pitching records. Or football without the number of yards gained, number of passes completed, lengths of passes, and so forth.
  • People in sports who do not see themselves as statisticianscontinually make decisions based on statistics: the manager who has to decide who is the best available pinch hitter in a given situation, measures  best  in terms of batting averages under similar circumstances.
  • If your interest is business and finance, think of the importance of stock market indexes; the
  • movement of commodity, stock, and bond prices; corporate profits or bond ratings; and other
  • financial indicators. Decisions to buy or sell are made on the basis of the information conveyed by these statistics.
  • In marketing, you need numbers and statistical methods to answer questions for making key decisions:
  • How many potential customers are there for a particular product or in a particular geographic
  • region?
  • How rich or how poor are your potential and actual customers?
  • What are the characteristics of your potential customers?
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Introduction to Statistical Reasoning

Uses of Statistics

  • Numbers are the basis for political decisions on what actions to take and which policies to accept, reject, or formulate. Government officials constantly make decisions based on numbers.
  • For example, the unemployment rate is watched by elected officials, administrators, and the public when deciding whether the government should take action to influence the economy:
  • Shall we start a job development program to reduce unemployment in a particular region?
  • Shall we pay more unemployment benefits for longer?
  • The Consumer Price Index (a measure of inflation)is used to evaluate and determine economic policy.
  • Government officials use it to evaluate how well current economic policies are working
  • Private companies use to make economic decisions. Example- increase wages.
  • Great advances in science, medicine, engineering, social and economic policy would not have been possible without the use of statistical methodology.
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Introduction to Statistical Reasoning

The  Lady with a Lamp  Was a Numbers Cruncher

  • Florence Nightingale (Nurse and Statistician) was appalled by the lack of medical and nursing care and the widespread presence of unsanitary conditions that she found in British army hospitals during the Crimean War(1853-1856).
  • She collected and analyzed extensive data on these conditions. Her remarkable study and its successful presentation in Parliament as part of her advocacy led to medical and nursing programs which greatly reduced human suffering.
  • She collected data that showed decisively and quantitatively that more soldiers died from diseases caused by unsanitary conditions than from battle wounds.
  • In January 1855, excluding men killed in action, the mortality rate  peaked at an annual rate of 1174 per 1000 .
  • This means that if mortality had persisted for a full year at the rate that applied in January, and if the dead soldiers had not been replaced, disease alone would have wiped out the entire British army in the Crimea.
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Introduction to Statistical Reasoning

The  Lady with a Lamp  Was a Numbers Cruncher

This graphic indicates the number of deaths that occurred from:

preventable diseases (in blue)

the results of wounds (in red),

due to other causes (in black).

  • Her remarkably effective lobbying, supported by then novel graphic presentations of the mortality statistics, brought an immediate response from the British public and government.
  • She was given government support to make sanitary reforms, which caused the death rate to drop dramatically.
  • Her statistical analyses were the key factor in motivating the modernization of the British armed forces medical programs and, subsequently, the introduction of a new standard of nursing and hospital care.
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Introduction to Statistical Reasoning

Esther Duflo: Social experiments to fight poverty

http://www.ted.com/talks/esther_duflo_social_experiments_to_fight_poverty.html

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Introduction to Statistical Reasoning

Summary

The use (and misuse) of statistical methodology is a double-edged sword. It can be used correctly, leading to advances in science, medicine, engineering, social and economic policy. Or they can be used incorrectly to manipulate and mislead.

“Finding the occasional straw of truth awash in a great ocean of confusion and bamboozle requires intelligence, vigilance, dedication and courage. But if we don't practice these tough habits of thought, we cannot hope to solve the truly serious problems that face us and we risk becoming a nation of suckers, up for grabs by the next charlatan that comes along.”

—Carl Sagan(1934-1996), Astrophysicist and advocator of skeptical inquiry

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Introduction to Statistical Reasoning

  • "Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write." H. G. Wells (1866 - 1946)
  • Is this true and if so, has that day arrived?
  • Unless we start teaching it at a much earlier age, the general public will not develop their statistical reasoning beyond what it is right now.
  • We live in a data-centric world. It is necessary that we are aware of all the types of possible error contained in data (from research studies, surveys etc.) and in the statistics derived from the data.
  • Scientific journalists need to go beyond simply reporting the findings of research scientists and clinical investigators that impact the health, life-styles and well-being of their readers.
  • This class aims to teach you how to tell good statistical methodology from bad and in the process, how to tell good scientific journalism from bad.
  • Last Paragraph of Bad Science - Quacks, Hacks and Big Pharma Flacks by Ben Goldacre, 2010
  • “Unmediated access to niche expertise is the future, and you know, science isn’t hard – academics around the world explain hugely complicated ideas to ignorant eighteen-year-olds every September – it just requires motivation.……….There’s no money in it, but you knew that when you started on this path. You will do it because you know that knowledge is beautiful, and because if only a hundred people share your passion, that is enough.”
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Introduction to Statistical Reasoning

How to get started

Reading the News Articles

Time Magazine NY Times Newsweek LA Times

CNN ABC News FOX MSNBC

Finding the source Journal Articles: Columbia Website under Libraries->E-Journals