Using Statistics from Florence Nightingale to Al Gore

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Using Statistics from Florence Nightingale to
Al Gore
NZAMT 2007
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Plan for today

• Health Statistics
• Florence Nightingale
• Dynamic Graphs - Gapminder
• UN Statistics
• Statistical Literacy
• Curriculum
• Data Lenses
• Environmental Statistics
• Expectation / Surprise
• Al Gore
• Correlation / Causation

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Task One

• Look at the graph you have been given
• What do you think?

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http//www.nightingaledeclaration.net/index.php?op
tioncom_contenttaskviewid37Itemid25
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Florence Nightingale

• Issue high mortality rate due to unsanitary
  conditions
• Collected data
• Invented Polar Area Diagram
• Intro of field hospitals

•    "To understand God's thoughts we must study
  statistics, for these are the measure of His
  purpose"

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Further Exploration

• http//www.math.yorku.ca/SCS/Gallery/milestone/sec
  1.html
• Milestones in the History of Thematic
  Cartography, Statistical Graphics, and Data
  Visualization

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The draft new curriculum

• Evaluate the effectiveness of different displays
  in representing the findings of an investigation
• Make and evaluate statements about the
  implications of data displays including possible
  causes of variation
• Evaluate the statistical processes used by
  others, including their sampling methods,
  measures of centrality and spread and the
  validity of their findings.

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The draft new curriculum

• Critically evaluate statistically based
  information in the media by considering the
  measures and data displays used, the statistics
  calculated and the claims made
• Consider statistically based claims by
  interpreting risk and relative risk, identifying
  possible sampling and non-sampling errors in
  polls and surveys
• Consider statistically based claims by
  evaluating a wide range of media reports,
  including polls, surveys, experiments and
  observational studies critiquing
  causal-relationship claims and interpreting
  margins of error.

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Possible lenses for viewing data displays

• I notice / I wonder
• Interest Groups
• Analysis Matrix
• THINKits
• Expectations / Surprises
• Tell a story

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Gapminder
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Tell a story

• Use the gapminder software, select a graph and
  use it to tell a story

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Downloads

• www.gapminder.org, click on Gapminder Tools then
  download button under each graph
• http//www.gapminder.org/downloads/applications/

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Your turn

• Look at the graph you have been given from the
  viewpoint of the region you represent

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An alternative method
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Expectations / Surprises

• Challenging preconceived ideas
• Exploring Centre and Spread

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UN Stats

• I notice
• I wonder
• Thinking matrix

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Link

• http//www.who.int/whosis/whostat2007_10highlights
  .pdf
• WHO WHO Statistical Information System
• http//www.who.int/whosis/en/

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Life expectancy at birth (years)

• Rationale for use
• Life expectancy at birth reflects the overall
  mortality level of a population. It summarizes
  the mortality pattern that prevails across all
  age groups - children and adolescents, adults and
  the elderly.
• Definition
• Average number of years that a newborn is
  expected to live if current mortality rates
  continue to apply.
• Associated terms
• A life table presents a set of tabulations that
  describe the probability of dying, the death rate
  and the number of survivors for each age or age
  group. Accordingly, life expectancy at birth is
  an output of a life table.
• Data sources
• Vital registration, census and surveys
  Age-specific mortality rates required to compute
  life expectancy at birth.

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• Methods of estimation
• WHO has developed a model life table based on
  about 1800 life tables from vital registration
  judged to be of good quality.
• For countries with vital registration, the level
  of completeness of recorded mortality data in the
  population is assessed and mortality rates are
  adjusted accordingly.
• Where vital registration data for 2003 were
  available, these were used directly to construct
  the life table. For countries where the
  information system provided a time series of
  annual life tables, parameters from the life
  table were projected using a weighted regression
  model, giving more weight to recent years.
  Projected values of the two life table parameters
  were then applied to the modified logit life
  table model, where the most recent national data
  provided an age pattern, to predict the full life
  table for 2003.
• In case of inadequate sources of age-specific
  mortality rates, the life table is derived from
  estimated under-5 mortality rates and adult
  mortality rates that are applied to a global
  standard (defined as the average of all the 1800
  life tables) using a modified logit model.

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• Disaggregation
• By sex, location (urban/rural, major
  regions/provinces).
• Comments
• The lack of complete and reliable mortality data,
  especially for low income countries and
  particularly on mortality among adults and the
  elderly, necessitates the application of
  modelling (based on data from other populations)
  to estimate life expectancy. WHO uses a standard
  method as explained above to estimate and project
  life tables for all Member States using
  comparable data. This may lead to minor
  differences compared with official life tables
  prepared by Member States.

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A look at environmental data

• Where would you like to live

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Environmental Statistics
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Al Gore

• An inconvenient truth
• http//www.climatecrisis.net/

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Some graphs

• Compare and Contrast it
• An inconvenient truth

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Correlation / Causation

• Power point

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Statistical Thinking
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• A statistician is a person who stands in a
  bucket of ice water, sticks their head in an oven
  and says "On average, I feel fine."
• K.Dunnigan

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• A mathematician is a blindfolded person in a
  dark room looking for a black cat which isn't
  there.
• Charles Darwin

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The draft new curriculum

• Evaluate the effectiveness of different displays
  in representing the findings of an investigation
• Make and evaluate statements about the
  implications of data displays including possible
  causes of variation
• Evaluate the statistical processes used by
  others, including their sampling methods,
  measures of centrality and spread and the
  validity of their findings.

47
The draft new curriculum

• Critically evaluate statistically based
  information in the media by considering the
  measures and data displays used, the statistics
  calculated and the claims made
• Consider statistically based claims by
  interpreting risk and relative risk, identifying
  possible sampling and non-sampling errors in
  polls and surveys
• Consider statistically based claims by
  evaluating a wide range of media reports,
  including polls, surveys, experiments and
  observational studies critiquing
  causal-relationship claims and interpreting
  margins of error.