Analysis of Variance (ANOVA) Overview

A set of flashcards focused on key concepts, terms, and principles related to Analysis of Variance, useful for understanding and preparing for exams on this topic.

Analysis of Variance (ANOVA)

A parametric statistical technique that determines if there are statistically significant differences between the means of three or more groups.

One-way ANOVA

A test conducted when a study has one independent and one dependent variable.

Two-Way ANOVA

An analysis involving two independent variables.

Factorial ANOVA

An extension of the two-way ANOVA that includes multiple factors with different levels.

Repeated-Measures ANOVA

A test used for data from studies where the same variable(s) is(are) measured repeatedly over time.

F statistic

A numerical value calculated in ANOVA that indicates group mean differences, considering variability within groups.

Null hypothesis

The hypothesis stating that no differences exist between group means.

p value

The calculated probability used to determine the significance of results in ANOVA.

Alpha (α)

The significance level set for a study, commonly at 0.05 or 0.01.

Assumptions of ANOVA

Conditions that must be met, including normal distribution, independent measurements, and equal variance among groups.

Homogeneity of variance

The assumption that different samples have equal variances.

Degrees of freedom (df)

The number of independent values or quantities which can be assigned to a statistical distribution.

Mean Square (MS)

The estimate of variance used in computing the F statistic in ANOVA.

Between-groups variance

Variance that represents the differences between groups being compared.

Within-groups variance

Variance that represents differences among individual data within each group.

Post hoc analyses

Further tests done after ANOVA to find specific group differences when significant results are obtained.

Newman-Keuls test

A type of post hoc analysis used to determine differences between group means.

Tukey Honestly Significant Difference (HSD) test

A post hoc test that compares all possible pairs of means.

Scheffé test

A versatile post hoc test used for comparing multiple groups.

Dunnett test

A post hoc test used to compare multiple treatment groups against a control group.

Randomized experimental design

A research design where participants are randomly assigned to groups.

Quasi-experimental design

Research design without random assignment to groups.

Comparative design

A study design that compares two or more groups.

F-ratio

The value calculated in ANOVA, representing the ratio of variances between groups.

Critical F value

The value obtained from F distribution tables used to determine if the results are statistically significant.

Research question in ANOVA

The specific query the researcher aims to address through the ANOVA.

Statistical significance

A determination that results are unlikely to have occurred under the null hypothesis.

Analysis of Variance calculations

The steps and methods used to compute ANOVA results.