T-Tests and Comparison of Means

Flashcards for reviewing lecture notes on t-tests, covering paired t-tests, false positives, two-sample tests, and related concepts.

Paired t-test

A type of t-test used to compare the means of two related groups, such as pre-treatment and post-treatment scores.

False Positive

Incorrectly rejecting the null hypothesis when it is actually true, also known as a Type I error.

Two-Sample t-test

A type of t-test used to compare the means of two independent groups.

Student's t-test

A statistical test used to determine if there is a significant difference between the means of two groups.

One-Sample t-Test

Compares a single sample mean to a known population mean or a hypothesized value.

Two-Sample t-Test

Compares the means of two independent samples to determine if there is a significant difference between them.

Paired Sample t-Test

Compares the means of two related samples, where each observation in one sample is paired with an observation in the other sample.

Null Hypothesis (H0)

The hypothesis that there is no significant difference between the means being compared.

Alternative Hypothesis (HA)

The hypothesis that there is a significant difference between the means being compared.

P-value

The probability of obtaining a test statistic as extreme as, or more extreme than, the one observed, assuming the null hypothesis is true.

Alpha (α) value

The threshold for determining statistical significance; typically set at 0.05, meaning a 5% chance of incorrectly rejecting the null hypothesis.

Type I Error Rate

The rate at which the null hypothesis is incorrectly rejected when it is true.