Explain the strengths and weaknesses of factorial designs.
Strengths:
- Allows for more precise hypothesises to be tested.
- Can include extraneous variables as IV (blocking).
- Identify interactive effects.
Weaknesses:
- Logistically difficult.
- Higher-order interactions are harder to interpret (or impossible).
Explain the concepts of main effect.
The influence of one IV on the DV.
Explain the concept of interaction effect.
The interactive effect of two or more IVs on a DV.
Describe the considerations made when deciding upon the appropriate experimental design.
- Review previous literature.
- Use of control group.
- Number of comparison groups.
- Pretesting.
- Within-participants, between-participants or mixed?
- Number of independent and dependent variables.
- Will it be approved by the IRB?
- Can you obtain participants? (animals or humans).
- Instruments needed.
Explain the importance of sample size.
Larger samples provide more accurate data and interpretations.
Explain why it is necessary to conduct a pilot study prior to data collection.
- Establishes clarity of instructions.
- Provides evidence that independent variable is being manipulated adequately.
- Familiarizes researcher with the procedure.
Explain the concept of statistical power (Beta).
The probability of correctly rejecting the null hypothesis, power of .80 is desired.
Sample size, alpha level and effect size (cohen’s d) influence power.
What is the cell? (factorial design)
Combination of levels of two or more IVs in a factorial design layout.
What is the cell mean? (factorial design)
The mean score of all the participants in a cell.
What is the marginal mean? (factorial design)
The mean of a row or column in the factorial design layout.
What is a pilot study?
A brief run-through of the entire experiment with a few participants prior to the actual collection of data.
