Lecture 4: Testing Hypotheses: Independent Sample t-test

Flashcards covering key vocabulary and concepts related to Independent Samples T-tests, study design, and hypothesis testing. These flashcards are designed to help you review your lecture notes and prepare for your upcoming exam.

Independent Samples T-Test

A test that compares the means of two independent groups.

Independent Data Observation

Each data sample is a separate observation.

Between Subjects Design

Each person contributes to a single condition.

Within Subjects Design

Everyone contributes to both conditions – repeated measures.

Between Subjects Design Definition

Two independent groups of data points where each participant is in a single group and contributes one data point.

Within Subjects Design Definition

Two dependent groups of data points where each participant completes two conditions and contributes two data points. Sometimes called ‘repeated measures.’

Two-Sample Hypothesis

A statement about the means of two different samples.

Two-Sample Null Hypothesis

A statement that the means of two different samples are the same.

When to use a t-test

Data must be interval or ratio type, assumptions must be met, and the data must have an interpretable mean and standard deviation.

Normality

Data are normally distributed.

Homogeneity of Variance

Groups have equal variance.

Welch's Test

Removes the assumption of equal variances.

Independent Samples T-Test Definition

The difference between the two means of two groups of data, all divided by the standard error of that difference.

Pooled Standard Deviation

A single standard deviation used to represent the variability in both groups, assuming that both groups have the same variability.

Levene’s Test for Homogeneity of Variance

Assesses the null hypothesis that different groups of samples are from populations with equal variances.

Welch’s t-test

Uses an unpooled measure of standard deviation, which is valid when the groups have different variances. The unpooled standard deviation is valid whether the groups have equal variances or not.

Paired Samples T-test

A test that compares the means of two dependent distributions – that is, when the same participants have contributed to each condition.

Paired Samples T-test Computation

Take the difference between each pair of samples and compute a one-sample t-test between the paired difference and zero.