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One Proportion: Can dogs small COVID?

ANATOMY OF AN ACTIVITY

BETH CHANCE- SAN LUIS OBISPO

(BCHANCE@CALPOLY.EDU)

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Overview

  • Background/Development process
    • Critical vs. Less critical decisions?
  • Activity introducing students to the logic of statistical inference using the one proportion scenario as I use it with my students
  • Discussion

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Materials

  • Pre-lab in advance
  • Google doc (make a copy)
  • One proportion applet (separate link)
  • Teacher’s guide
    • Commentary on google doc
    • Alternative from STUB website (shortened)
    • Example pre-lab
    • Example post-quiz

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Learning Goals

  • Apply the 6-step process
  • Analyze a research question involving one binary variable
  • Logic of statistical inference
    • Simulation-based inference

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What’s come before

  • Introduction to Randomness – Monty Hall (later session) (One day)
    • Defining probability as long-run relative frequency
  • Distribution and Variability (One day)
    • Observational unit, Variable
    • Quantitative: Shape, Center, Variability
  • Maybe a day where we go through an example together
  • Between days 3 and 4: Prelab

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Lab 1: Prelab

POSSIBLE ACTIVITIES

  • Watch a video
  • Read the background
  • Answer definition questions (what is the observational unit, what is the variable/type, statistic vs. parameter?)
  • Simple calculations
  • Technology practice
  • Critique study design/research question
  • >> Aim for class time to focus on “new” content…

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Lab 1: Pre-lab

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Lab 1: Pre-lab

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To the activity!

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Choice of context

  • Videos
  • Significance (how obviously)
  • Meaningful?
  • Sample size
    • May want to start small for tactile simulation
      • Also helps students be skeptical of the results (“but there were only 16”)
    • Option: start with a “small scale” version
  • Student data
    • May not start with student data but very soon (help distinguish between “observed” and “simulated” results

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Key features

  • Scaffolding student engagement
  • Focusing on the concept
    • Explaining their reasoning = describing the picture they have created
  • No real terminology/symbols
    • Hypotheses all in words (two possible explanations, p-value eliminates the ‘random chance’ explanations)
    • Some language to consider: chance model, null distribution, plausible vs. probable vs. possible, what-if distribution, could-have-been results, 3S process (statistic, simulation, strength of evidence)
    • Start with number of successes? But then think about when to transition to proportions
  • Start with a tactile simulation/students are a dot in the graph
  • Start with research question, end with a conclusion/evidence

Use language that is meaningful to the students, that you can refer back to throughout the course

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Resources

  • Applets:

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  • Other examples/variations:
    • Day 5: Investigation 2 Word file or Google doc
    • Lab 1
    • Stat 217 Lecture Notes
  • Early introduction to inference (middle school):
    • If you only have one hour… Statistics Teacher (ASA)

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