Quantitative Research Methods - Lecture 9

These flashcards cover key vocabulary from the lecture on non-parametric models and their statistical applications.

Non-parametric models

Statistical tests that do not assume a specific distribution of the data.

Parametric tests

Tests that make assumptions about the parameters of the population distribution, such as the mean.

Distribution free tests

Another term for non-parametric tests, indicating they are less reliant on strict assumptions.

Kruskal-Wallis test

A non-parametric alternative to one-way ANOVA, used to compare three or more independent groups.

Friedman’s ANOVA

A non-parametric test used for comparing three or more related groups.

Medians

The middle value in a data set when the values are organized in ascending or descending order.

Outliers

Data points that differ significantly from other observations; can affect parametric tests.

Ranking scores

A process in non-parametric tests where data points are assigned ranks instead of using their actual values.

Significant difference

A statistical term indicating that the observed effect is unlikely to have occurred by chance alone.

Population

The entire group of individuals or instances about whom we hope to learn.