Section 2 - Analysis & Critique Vocabulary

Independent Variable

The predictor or manipulated variable that the researcher controls or assigns

Dependent Variable

The outcome or response variable that is measured to assess the effect of the independent variable

Null Hypothesis

No difference or relationship exists between the independent and dependent variables

Type I Error (False Positive)

When a researcher concludes there is a difference or effect when none actually exists. Null hypothesis is rejected when it should be retained.

Type II Error (False Negative)

When a researcher fails to detect a real effect or difference that truly exists. Statistically, this means the null hypothesis is retianed when it should be rejected.

Internal Validity

Refers to how well a study answers its original research question

External Validity

Refers to how well the findings can be generalized beyond the study sample

Paired or Repeated Measures Analyses

Used when the same subjects are measured across conditions or time.

Correlation

The relationship between two continuous variables, not causation.

T-test

Assess differences between 2 groups (1 comparison)

Paired t-test

Compares the means of two related measurements from the same participants.

Unpaired t-test

Compares the means of two independent groups (different participants in each group)

One-Way ANOVA

Compares the means of three or more independent groups

One-Way Repeated Measures ANOVA

Compares the means of three or more related measurements from the same participants.

Two-Way ANOVA

Compares the means across combinations of two independent factors using different participants in each gorup

Two-Way Repeated Measures ANOVA

Compares the means across combinations of two factors when at least one factor is measured repeatedly in the same participants.

Statistical Power

The probability that the statistical test will correctly reject a false null hypothesis