1. Review
This template can be used as a starter file for presenting training materials in a group setting.
Sections
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Notes
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Keep in mind the font size (important for accessibility, visibility, videotaping, and online production)
Coordinated colors
Pay particular attention to the graphs, charts, and text boxes.
Consider that attendees will print in black and white or grayscale. Run a test print to make sure your colors work when printed in pure black and white and grayscale.
Graphics, tables, and graphs
Keep it simple: If possible, use consistent, non-distracting styles and colors.
Label all graphs and tables.

2. Experimental Designs Requirements: Types
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 Treat 2
Between Groups
Within Groups:
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

7. question 22 IVs DVs Knowledge Score in test
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

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

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

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