Research methods Spring + Summer term Flashcards
Binomial test (assumption)
Nominal data
Single dichotomy
Scores come from a random sample of population
Data is independent
Chance level is known
Chi square test of independence (assumption)
Nominal data
Two dichotomies
Scores come from a random sample
Independent data
N is at least 40
Expected frequency of each category is at least 5
Chi - square test of independence (non - parametric alternative)
Fisher’s exact test
Chi - square goodness of fit test (assumption)
Nominal data
Multiple levels of a single dependent variable
Scores come from a random sample
Independent data
Each category has an expected N of 5 or above
One sample t - test (assumption)
Independent data
Continuous data
Normal distribution (Shapiro-Wilk test)
One sample t - test (non-parametric alternative)
One sample Wilcoxon
Independent samples t - test (assumption)
Independent data
Interval data
N is equal to or bigger than 12
Normal distribution (Shapiro - Wilk test)
Homogeneity of Variance (Levene’s test)
What is Homogeneity of variance
Variance of one condition should be similar to the variance of another condition.
Independent samples t - test (non - parametric alternative)
Mann Whitney U - Test
Paired samples t - test (assumption)
Interval data
Within samples design
N is equal to or bigger than 12
Differences between conditions are normally distributes
Paired samples t - test (non - parametric alternative)
Wilcoxon signed ranks test for related samples
Control variable
Things you intentionally keep the same in your experiment
Control condition
A separate condition that helps you understand the role of the IV, or helps you rule out the alternative explanations for your result.
Extraneous variable
Not controlled in the experiment
Could have an effect on the DV
Confounding variable
Vary systematically with the IV to influence the DV
Are likely to influence the results