Research Design Flashcards
Types of Design
ANOVAs
Alpha level
The chance of making a type I error
Type 1 and 2 Errors
Type I Error: Detect a significant difference when there is not one, chances of making a type I error = the alpha level
Type II Error: Fail to detect a significant difference when there is one
Measures of Central Tendency
Mean: average
Median: response at the center of the distribution
Mode: most frequent response
Effect Size
- Cohen’s D
- Calculation: d = (M1 – M2) / pooled SD
- Measures whether the independent variable has an effect on the dependent variable
- Other stats related to effect size: Correlations, Standardized Mean Differences, Odds ratio
Reliability
See if test measures accurately
Cronbach’s alpha (Reliability coefficient - internal consistency)
Validity
See if test measures what it is supposed to measure
Double-Blind Study
- Multiple participant groups assigned
- Neither researcher nor participants know which group they are in
Distribution Curve
Standard Error of Estimate and Measurement
Percentile Ranks
Sample Size
- Sample needs to represent the larger population
- Sample needs to be large enough to be high-powered but not so large that it is wasting resources that are not necessary to find a meaningful difference
Statistical Power
- The probability of avoiding a type II error (failure to detect a meaningful difference in the sample)
- Typically set at 80%
- Too much power = tests are too sensitive to true effects
Instrumentation
- Threat to internal validity
- E.g., you are relying on an expert rater’s ratings for your dependent variable and find that the rater’s accuracy changes over time