Comparing Groups

Question 1

What are parametric tests

Answer 1

They are statistical tests that make certain assumptions about the parameters (e.g. mean and variance) of a population distribution from which the sample is drawn

These tests are more precise when assumptions are met

Question 2

What are the assumptions of parametric tests

Answer 2

Normality: data should follow a roughly normal distribution (quantile quantile plot)

Homogeneity of variance: the variances within each group being compared should be roughly equal (Levene’s test)

Independence: the observations should be independent from each other

Question 3

What are some common parametric tests used

Answer 3

One sample t-test

Independent two-sample t-test

Paired t-test

One/ Two way ANOVA

Repeated measures ANOVA

Mixed design ANOVA

Question 4

What are non-parametric tests

Answer 4

Statistical methods that do not assume a specific distribution for the data
E.g required if parametric tests are violated or when dealing with ordinal data or small sample sizes

Question 5

What are the assumptions of non-parametric tests

Answer 5

Independence of observations

Personal or continuous data

Random sampling

Question 6

What are some non-parametric tests

Answer 6

Mann-Whitney U test

Wilcoxon signed-Rank test

Kruskal-Wallis H Test

Friedman test