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Making Predictions with Linear Models: A Murder Mystery Case Study

Author(s): Miranda Chen Musgrove1, Lisa A. Corwin1, Andrew Martin1

University of Colorado, Boulder

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Summary:
This Swirl lesson will introduce two main concepts to students: 1) the idea of uncertainty around linear slopes versus individual values and 2) predicting values using linear models.

Licensed under CC Attribution-ShareAlike 4.0 International according to these terms

Version 1.0 - published on 31 May 2021 doi:10.25334/3BW4-YR61 - cite this

Keywords

  1. data visualization
  2. linear models
  3. case study teaching
  4. uncertainty
  5. prediction
  6. Confidence intervals

Alignments

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  2. Audience Level
  3. Activity Length
  4. Inclusive Pedagogy for Life Science Education
  5. Open Science and Education Practices Ontology
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Description

Students will be presented with a crime scene investigation/murder mystery challenge where they need to create a linear model and use it to determine a y-value (time of death) of a particular x-value (hypoxanthine concentration in a posthumous eye). Students will be encouraged to develop hypotheses for what happened to the dead victim--if the individual was murdered or not. Data for hours after death and hypoxanthine concentration will be provided. They will be asked to calculate the time of death with both mean confidence intervals (CIs) and individual CIs for the data around the slope. Lastly, students will interpret results to then evaluate their hypotheses and determine whether they have enough evidence to conclude that a murder took place or not.

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