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Experiment Design 2: Validity. Martin Ch 2. Demonstration: how to design a bad experiment. How can we measure intelligence?. Conclusion validity. Statistical Appropriate statistics? Internal Really the cause? Construct (Measure) Measure what it is supposed to measure? External

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Presentation Transcript
demonstration how to design a bad experiment
Demonstration: how to design a bad experiment
  • How can we measure intelligence?
conclusion validity
Conclusion validity
  • Statistical
    • Appropriate statistics?
  • Internal
    • Really the cause?
  • Construct (Measure)
    • Measure what it is supposed to measure?
  • External
    • Will it generalize? (e.g., sampling)
statistical validity
Statistical Validity
  • Run any inferential statistics?
  • Run appropriate inferential statistics?
  • Assumptions of tests are met?
    • Normality
    • Homogeneity of variance
    • Independence of variance
threats to internal validity
Threats to internal validity
  • Participant variables
    • History (different past experiences)
    • Maturation (more past experiences)
    • Self-selection differences
    • Mortality (some participants disappear)
  • Selection process artifacts
    • Testing (determining group changes them)
    • Statistical regression (just different by chance the first time)
construct measure validity
Construct (measure) validity
  • Face
    • Sounds plausible on the face of it?
  • Content
    • Content details seem appropriate?
  • Predictive
    • Predicts things that it should predict?
  • Concurrent
    • Correlated with things that should be related? (but not too highly!)
external validity
External validity
  • Experiment versus real life:
    • Participants
    • Tasks
    • Situations
  • Tradeoffs between internal + external validity
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