Tuesday, week 6

1
Tuesday, week 6

• Arney on Statistics and Uncertainty
• Zita on sorting wheat from chaff (Critical
  thinking tools)
• Mammograms and Mind tools (Gigerenzer)
• Baloney Detector Kit (Sagan)
• Theory-laden facts (Kuhn)
• Strong objectivity and situated knowledge
  (Harding)
• Looking ahead

2
From Harpers Index

• Number of new U.S. soldiers the Army would need
  in 2006 to replenish ranks abroad 80,000
• Percentage of this goal it expects to meet 9.9
• Percentage change since 1996 in the average
  recruitment cost per new U.S. soldier 84

3
From Harpers Index

• Number of Palestinian communities that will be
  surrounded by the new Israeli security fence on
  at least three sides 53
• Chance that a German says Israels treatment of
  Palestinians is the same in principle as how
  Nazis treated Jews 1 in 2
• Factor by which the unemployment rate among
  Jewish immigrants to Germany exceeds the national
  average 3.5
• Percentage of Germans who say, about the Nazi
  era, that one should not poke around in old
  wounds 60

4
From Harpers Index

• Total annual spending controlled by functionally
  illiterate U.S. consumers 414,000,000,000
• Chance that a teacher in a U.S. public school is
  a man 1 in 5
• Average percentage of students in N.Y. States
  majority-white districts who graduate in four
  years 79
• Average percentage who do so in districts where a
  majority of students are black or Latino 40

5
From Harpers Index

• Ratio of the worlds reconstruction aid given to
  postwar Kosovo, per capita, to that given postwar
  Afghanistan 231
• Ratio of the number of peacekeeping troops in
  Kosovo, per capita, to that in Afghanistan 241
• Amount the U.S spent last year on mosquito nets
  to fight malaria in Africa 4,000,000
• Amount it paid a consultancy to conduct social
  marketing of mosquito nets 7,900,000

6
From Harpers Index

• Percentage change in the average monthly price of
  oil during the Carter Administration 85
• Percentage change during the presidency of George
  W. Bush, before Katrina 107
• Number of consecutive years that the U.S. median
  income has failed to increase 5
• Number of consecutive years that the percentage
  of Americans living in poverty has increased 4

7
(No Transcript)
8
(No Transcript)
9
(No Transcript)
10
(No Transcript)
11
Source Ross Douthat, Does Meritocracy Work?
Atlantic Monthly, November, 2005.
12
(No Transcript)
13
(No Transcript)
14
(No Transcript)
15
(No Transcript)
16
Sophomores Passing WASL in 2005
42.8
17
Current Sophomores Who Wont Graduate
57.2
If the present situation persists.
18
(No Transcript)
19
John Tukey Exploratory Data Analysis,
1977 Edward R. Tufte Visual Display of
Quantitative Information, 1983 Envisioning
Information, 1990 Visual and Statistical
Thinking Displays of Evidence for Decision
Making, 1997 Visual Explanations Images and
Quantities, Evidence and Narrative, 1997 The
Cognitive Style of PowerPoint, 2003
20
Break time
21
Zita on Sorting wheat from chaff (Critical
thinking tools)

• Mammograms and Mind tools (Gigerenzer)
• Baloney Detector Kit (Sagan)
• Theory-laden facts (Kuhn)
• Strong objectivity and situated knowledge
  (Harding)

22
Mammograms Gigerenzers claims

• Risks gt benefits
• Doctors tell patients that a positive mammogram
  means
• she has cancer and
• she needs surgery, preferably a mastectomy
• Mammogram radiation causes breast cancer.

23
Mammograms ask a doctor

• Test results are NOT simply positive and
  negative
• but a range of categories
• Category 0 - Need additional imaging evaluation.
  Most category 0 findings are shown to be benign
  after additional imaging is completed.
• Category 1 - Negative
• Category 2 - Benign finding, noncancerous
• Category 3 - Probably benign finding,
  short-interval follow-up suggested
• Category 4 - Suspicious abnormality, biopsy
  considered
• Category 5 - Highly suggestive of malignancy,
  appropriate action needed
• Suspicious abnormality probably does NOT mean
  you have cancer! Instead of rush to surgery, Drs
  recommend
• Second, targeted mammogram (spot check)
• Needle biopsy
• Surgical biopsy
• Lumpectomy or mastectomy

24
What about radiation risk?

• Gs target group is women in their 40s
• Mammogram radiation was more dangerous 35 years
  ago (when target women were teenagers), and is 10
  times lower now
• High radiation took 20 years to cause cancer
  (p.69)
• Most women in their 40s were not getting
  mammograms 20 years ago
• GG says 30/100,000 women get cancer from
  mammograms - or did, when radiation dose was
  high?
• (By the way) mammograms save 100 lives per
  100,000 women

25
Breast cancer pamphlets Gs claims

• Uncertainties are not acknowledged
• Risks of screening are not discussed
• Detection prevention?
• Mammograms can be positive or negative
• Mammogram radiation causes cancer
• Early detection causes more harm than good, and
  usually leads to unnecessary surgery (p.58) (but
  about half of ductal carcinoma in situ will
  progress to malignancy, if untreated! p.57)
• Lets look at the doctors pamphlets

26

• http//www.cancer.gov/cancer_information/cancer_ty
  pe/breast/

27

• http//www.cancer.gov/cancertopics/pdq/screening/b
  reast/Patient/page4

28

• http//www.cancer.gov/cancertopics/pdq/screening/b
  reast/Patient/page4

29
Breast cancer pamphlets

• Uncertainties are acknowledged
• Risks of screening are explicit
• Detection ? prevention
• Some of Gigerenzers claims appear to be
• Internally inconsistent
• Inconsistent with practice and statistics
• Supportive of his bias more than facts
• Red flags which make his other claims suspect

30
Baloney Detector can help (Sagan)

• Counting the hits and forgetting the misses. Ex
  One study shows
• Red herrings and straw men Emphasized
  3/10,000 (or 3/100,000?) women will develop
  (mammography-) induced breast cancer (p.70)
  Underemphasized That was when radiation levels
  were 10 x higher. 100/100,000 lives are saved by
  mammography (p.60)
• Separate variables women in their 40s are at
  very low risk of mammogram-induced cancer
• False dichotomy There is a trade-off between
  false positives and false negatives (p.70) But
  more highly skilled radiologists should minimize
  both of these.

31
Tools for skeptical thinking (Sagan.210)

• Independent confirmation of facts
• Arguments from authority carry little weight
• Spin multiple hypotheses
• Suspect your favorite hypothesis
• Quantify. Predict. Test.
• Every link in the argument chain must work.
• Occams razor simpler explanation more likely
• Untestable hypotheses carry little weight
• Control experiments and double-blind studies
• Separate variables

32
Logical Fallacies (Sagan.212)

• ad hominem attacking the arguer, not the
  argument
• Argument from adverse consequences
• Appeal to ignorance (absence of evidence ?
  evidence of absence
• Special pleading
• Begging the question, or Assuming the answer
• Counting the hits and forgetting the misses
• Misunderstanding statistics
• Inconsistency
• non sequitur it doesnt follow

33
Logical Fallacies (Sagan.213)

• post hoc, ergo propter hoc it happened after,
  so it was caused by
• Confusion of correlation with causation
• False dichotomy, or excluded middle (black and
  white)
• Slippery slope
• Short-term vs long-term
• Straw men and red herrings
• Suppressed evidence or half-truths
• Weasel words

34
Theory laden facts can help (Kuhn)

• Facts ? Truth
• Knowledge is CREATED, not discovered
• What counts as facts? What counts as a good
  question to investigate?
• Facts depend on language, beliefs, framework,
  , e.g. paradigm.
• Ex Early detection of breast cancer does more
  harm than good what counts as harm and good?

35
Strong objectivity can help (Harding)

• Knowledge (including science) is created by
  humans, therefore subjective (Kuhn)
• STRONG OBJECTIVITY first, acknowledge our
  subjectivities
• Biases, language, culture, values, limited
  perspectives
• Get input from people with different perspectives
• GOALS Better knowledge and understanding
• Empirically more adequate (Kuhn)
• Less partial and distorted descriptions
  explanations
• Ex Early detection of breast cancer does more
  harm than good from whose perspective?

36
Good statistics can help (Gigerenzer)

• Use natural frequencies more often than
  probabilities (though probabilities ARE sometimes
  simpler)
• Use absolute risks more than relative risks
• Specify your reference class
• Acknowledge prevalence of false positives and
  false negatives
• Overcome the illusion of uncertainty dare to
  know

37
Take-home messages

• Use statistics honestly and clearly
• Beware facts ? Truth
• Know the contexts and limitations of data and
  knowledge-creation
• Acknowledge your bias, agenda, and standpoint, as
  an analyst and as an author
• Avoid logical fallacies
• Use tools for skeptical thinking
• Encourage readers, patients, doctors, etc. to
  reason, not to blindly use numbers or formulae

38
Looking ahead
39
Invitation to women interested in physics or
teaching

• Expanding Your Horizons for middle-school girls -
  GOALS
• Increase young womens interest in
• mathematics, science and technology.
• Provide an opportunity to meet women
• working in non-traditional fields.
• Foster awareness of careers for women
• in mathematics and science-related areas.
• This Saturday 5 Nov. from 8am-noon at SPSCC
• Zita will present a workshop on Magnet Magic
• If you are interested in helping at this
  workshop, please see me after class or email
  zita_at_evergreen.edu
• http//www.starjumper.org/aboutus.html

40

• http//www.cdc.gov/cancer/nbccedp/info-bc.htm