Stat 151 Module 9: ANOVA

These flashcards cover the key concepts and vocabulary from the Stat 151 lecture on ANOVA.

ANOVA

Analysis of Variance; a statistical method used to determine if there are statistically significant differences between the means of three or more independent groups.

Pooled t-test

A statistical test used to determine if two independent samples have different means, assuming equal variances.

Null Hypothesis (H0)

The hypothesis that states there is no effect or difference; in ANOVA, it states that all population means are equal.

Alternative Hypothesis (Ha)

The hypothesis that states there is an effect or difference; in ANOVA, it states that at least one population mean is different.

Type I error

The error made when the null hypothesis is true but is incorrectly rejected.

F-test statistic

A ratio used in ANOVA to compare the variability between group means to the variability within each group.

Mean Square Error (MSE)

An estimate of the variance within the groups in ANOVA; calculated as the sum of squares for error divided by the degrees of freedom.

Mean Square Treatment (MST)

An estimate of the variance between the groups in ANOVA; calculated as the sum of squares for treatment divided by the degrees of freedom.

p-value

The probability of observing the test results under the null hypothesis; used to assess the strength of evidence against the null hypothesis.

Degrees of Freedom

The number of independent values that can vary in an analysis; calculated differently for MST and MSE in ANOVA.

Normal distribution

A probability distribution that is symmetric about the mean, depicting that data near the mean are more frequent in occurrence.

Independent populations

Populations in which the selection or characteristics of one group do not affect the other groups.

Significance level (B1)

A threshold used in hypothesis testing to determine whether to reject the null hypothesis, commonly set at 0.05.

F-distribution

A family of continuous probability distributions that arise frequently in ANOVA tests and is characterized by two sets of degrees of freedom.

Equal variability

An assumption in ANOVA that all groups have the same variance.