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Review

Review . Experimental Designs. Requirements: Manipulation of Conditions or Treatments Control for confounding variables Types Between Subjects Within Subjects Larger N Small n . Between Groups IV. Random assignment to treatment groups

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Review

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  1. Review

  2. Experimental Designs • Requirements: • Manipulation of Conditions or Treatments • Control for confounding variables • Types • Between Subjects • Within Subjects • Larger N • Small n

  3. Between Groups IV • Random assignment to treatment groups • Distribute evenly across levels of IV (e.g. treatment groups) individual differences among participants • Minimize impact if these difference in DV

  4. Within Groups IV • All participants receive all levels of IV • No individual differences across participants as potential confounds, therefore Randomnization is not needed (or possible) • Bias: Order effects: carry-over, fatigue • Counterbalancing (randomly assigned

  5. Within Groups Design • More statistical power than Between Groups: • With same sample size, more observation per condition N=40 Treat 1 Treat 2 • Between Groups 20 20 • Within Groups: 40 40 • Less variability across groups, therefore les sampling error (same individuals) and the higher the chance that p.alpha • Source of bias: crossover effects- order and fatigue

  6. question 22 • IVs • Treatment: Tech vs. lecture –True IV, BW- random assignment • Gender : M F Quasi-Exp BG • DVs Knowledge Score in test • Design 2x2 factorial, between groups- quota

  7. Analyses • ANOVA P values • Main Effect 1 p<.05 Gender • Main Effect2 p>.05 Lesson Type • Interaction Effect p<.05 Interaction

  8. Main Effects • Girls scored better on test than boys (regardless of type of instruction) • Boys score = 75Girls score = 86 p= <.05 • There is no difference in test scores between the Tech and Lecture lesson groups (regardless of gender) • Tech Avg 82.5 Lecture Avg 78.1 p>.05 ANOVA – for main effects

  9. Interaction effect • Boys • boys in Tech G > boys in Lecture group • Girls • girls in Tech G = girls in Lecture group Tech Lecture Boys 80 70 p<.025 Girls 85 87 p>.025 ANOVA for interaction effect --- followed by Test of simple effects – two T-tests; one per gender

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