Comparing Two Means and T-Tests

A set of flashcards covering vocabulary and key concepts related to T-tests, experimental design, and statistical assumptions.

T-test

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

Independent T-test

A T-test that compares two means from independent observations, where values are not connected.

Dependent T-test

A T-test that compares two means based on related observations, where the samples are paired or matched.

Effect Size

A quantitative measure of the magnitude of the difference between two groups.

Assumptions of the T-test

Conditions required for valid T-test results, including normal distribution and equal variances in populations.

Homogeneity of Variances

An assumption that states the variances among groups being compared should be approximately equal.

Null Hypothesis

The hypothesis stating that there is no effect or difference; it is tested in statistical analysis.

Standard Error

An estimate of the variability of a sample mean from the true population mean.

Paired T-test

A T-test that measures the same individuals multiple times, allowing for a direct comparison of the means.

Variance

A statistical measure that represents the degree of spread in a dataset.

Random Sampling

The process of selecting a subset of individuals from a population where each individual has an equal chance of being chosen.

Controlled Experiment

An experiment where one variable is changed while others are kept constant to observe the effect on a response variable.

Pearson's Correlation

A statistical measure that evaluates the strength and direction of the linear relationship between two variables.

t Statistic

A ratio that calculates the difference between group means divided by the standard error of the difference.

Mann-Whitney Test

A nonparametric test used instead of the dependent T-test when its assumptions are not met.

Wilcoxon Signed-Rank Test

A nonparametric test used instead of the independent T-test when its assumptions are not met.