Parametric and Non-parametric Tests

Start with an overview

The mind map on parametric tests for one and two populations is a starting point. It organizes tests by sample size and by independent or paired populations, with z-tests and t-tests included. Use its branches to see how the choices are grouped before looking at the details of an individual test.

The mind map “Parametric Test” also refers to non-parametric tests and their assumptions about population distributions. Read it alongside the overview to compare the kinds of questions the resources raise.

Check assumptions and normality

The quiz “Parametric assumptions and tests” asks about normal distributions, equal variances and standard error. After studying the maps, use the quiz to check which terms you can recognize and which ones you want to look at again. A lecture mind map also points to ways of testing assumptions using SPSS, including the Kolmogorov-Smirnov test and Levene’s test.

The flashcards on normality and parametric versus non-parametric statistics ask about ways to determine normality, including a normal probability plot and the Shapiro-Wilk test. The “Shapiro-Wilk test” deck offers questions about the test itself and how to report it.

Study individual tests

The “Levene's test” flashcards ask about significance and which row of a t-test table to read. Another deck covers normality and the z-test, including questions about its formula and tails. For tests of relationships, “Tests of relationships: Parametric” asks about Pearson Correlation and the Interclass Correlation Coefficient, including their limitations.

Place the topic in the unit

This page is one section of the unit Common Statistical Tests (t-tests, Chi-Square, Non-parametric) in Statistics and probability. Its maps, quiz and flashcards give you ways to work through the test choices and assumptions listed here. Return to a map after the quiz, then choose a flashcard deck to explore a test in more detail.