Introduction to Analyzing Rich Data Sets

• Students use statistical data and tools from GapMinder.org, Data360, ManyEyes, Baseball-Reference, the US Government and the like to solve messy problems:
  • collect data and record results,
  • organize the data,
  • make scatterplots,
  • fit the curves to the appropriate parent function
  • interpret the results,
  • proceed to model, predict, and make decisions and critical judgments.
• In doing so they will meet several members of the elementary-functions family, and use them to model the data.
• The lesson will focus on why we fit functions to data, how to critically evaluate a fit, and what this process can tell us about our world.
• Discuss causality and correlation
• Hypothesize processes that could explain the observed relationship
  • Why is population vs. time exponential?
  • Why do life expectancy and per capita income track each other as well as they do? What could explain the discrepancy?
  • Why has life expectancy in the US grown steadily during the century? Why does the rate of growth change the way it does?
• This segues into individual investigations that involve modeling a real-world question with linear and quadratic functions and solving for values.

 

Outline

Put pictures of each elementary function family up on the blackboard.

Set students loose on a large collection of rich, interesting data sets, including simple transformations (i.e. WorldPopulation and log(WorldPopulation) will both be accessible variables).

Whenever students find an interesting relationship -- one that fits