4.1

Vocabulary flashcards derived from a lecture on T tests and ANOVA, emphasizing key concepts, terms, and definitions used in statistics.

T test

A statistical test used to compare the means or average scores of two groups.

One Sample T test

Compares the sample mean to a population mean.

Independent Samples T test

Used when comparing two completely separate groups or conditions.

Paired Samples T test

Used when comparing repeated measures from the same participants.

Assumptions of T tests

Include independence, normality, and homogeneity of variances.

Null Hypothesis (H0)

States that there is no difference between the group means being compared.

Alternative Hypothesis (H1)

Indicates that there will be a difference in the average score between the two groups.

Independence of Observations

Scores in the groups must be independent of one another.

Normality

The dependent variable should fit a bell curve distribution.

Homogeneity of Variance

Variances within each group should be roughly equal.

Levene's Test

A test used to assess the homogeneity of variances.

Cohen's D

An effect size measure that indicates the strength of the difference between two means.

P value

The probability that the observed results would occur by chance under the null hypothesis.

Statistical Significance

Occurs when the P value is less than the alpha level (commonly set at 0.05).

Effect size

Quantifies the size of the difference between groups, indicating practical significance.

One-Way ANOVA

An extension of the T test used when comparing the means of three or more groups.

Type I Error

The incorrect rejection of a true null hypothesis, indicating a false positive.

Family-wise Error Rate

The probability of making one or more Type I errors when conducting multiple comparisons.

Post Hoc Tests

Further tests conducted after an ANOVA to identify specific group differences.

Tukey's HSD

A post hoc test used to find the means that are significantly different from each other.

Bonferroni Correction

A method to control for Type I error by adjusting the significance level when conducting multiple tests.

QQ Plot

A graphical tool used to assess whether a dataset follows a normal distribution.

Shapiro-Wilk Test

A statistical test for checking the normality of data.

Eta Squared (η²)

A measure of effect size for ANOVA that indicates the proportion of variance explained by an independent variable.