Learn: Experimental Psychology Test 3

Independent Groups Design

A between-subjects design where the single IV is manipulated and equivalent groups are formed through random assignment.

Matched Groups Design

A between-subjects design where participants are matched on a specific variable before assignment to conditions.

Ex Post Facto / Nonequivalent Groups Design

A between-subjects design where the IV is a non-manipulated subject variable where random assignment is impossible.

Repeated Measures Design

A within-subjects design where all participants participate in all levels of the IV.

Factorial Design

A research design including two or more independent variables tested simultaneously.

Mixed Factorial Design

A design with at least one between-subjects factor and at least one within-subjects factor.

P × E Factorial Design

Includes at least one person/subject variable and at least one manipulated environmental variable.

Two-Level Independent Groups Statistical Analysis

Independent samples t-test.

Multilevel Independent Groups Analysis

One-way ANOVA for independent groups.

Multilevel Repeated Measures Analysis

One-way ANOVA for repeated measures.

Factorial Designs Statistical Analysis

Two-way or multi-way ANOVA depending on the number of IVs.

Why ANOVA Instead of Multiple t-Tests?

Conducting multiple t-tests with 3+ groups rapidly inflates the Type I error rate.

Post-Hoc Tests (e.g., Tukey's HSD)

Pairwise comparisons computed between all condition levels to identify which pairs of means differ significantly in between-subjects designs.

Contrasts

Targeted, planned comparisons commonly used for within-subjects conditions.

Rule for Interpreting Post-Hoc Tests or Contrasts

You are only allowed to interpret them if the overall omnibus ANOVA test reveals a statistically significant effect (p < .05).

Mueller & Oppenheimer (2014) Note-Taking Study

Single-factor independent groups design comparing laptop vs. handwritten note-taking across 5 TED Talks.

Encoding Hypothesis

Processing that occurs during the act of note-taking improves learning and retention.

External Storage Hypothesis

The ability to review material later is beneficial, even when reviewing someone else's notes.

Generative Note-Taking

Summarizing and paraphrasing that forces deeper processing of lecture concepts, leading to superior memory.

Laptop Note-Taking Mechanism

Leads to shallow, non-generative verbatim transcription because typing speed exceeds handwriting speed.

Benefits of Adding More Than 2 Levels of an IV

Discovers nonlinear effects (e.g., Yerkes-Dodson Law) and rules out alternative explanations.

Bar Graphs

Used when the independent variable plotted on the X-axis is categorical or discrete.

Line Graphs

Used when the independent variable on the X-axis is continuous, or in factorial designs where non-parallel lines show interactions.

Placebo Control

Participants receive an inactive substance or sham procedure while believing they are receiving an active treatment.

Wait List Control

Participants are evaluated during an untreated waiting period and then receive the intervention after the study concludes.

Yoked Control

Each control participant is paired with an experimental subject and receives the exact same session duration without the active treatment.

Counterbalancing

Required in repeated measures (within-subjects) designs to control for sequence or order effects.

Reading Factorial Notation

Digits indicate the number of IVs, numerical values indicate levels, and total conditions equal the product of the digits.

Main Effect

The overall effect of one single independent variable on the DV, averaging across all levels of the other IV(s).

Interaction Effect

Occurs when the effect of one IV on the DV depends directly upon the level of another IV.

Effect of Interaction on Main Effects

A statistically significant interaction qualifies the interpretation of any significant main effects, requiring the interaction to be interpreted first.

ATI Design (Aptitude × Treatment Interaction)

A P × E design applied specifically to educational research, combining a student's personal attribute and instructional treatment.

Ceiling Effect

Scores cluster at the maximum limit of a measurement scale because the experimental task is far too easy.

Floor Effect

Scores cluster at the minimum limit of the scale because the experimental task is far too difficult.

Origin of ANOVA

Invented by Sir Ronald Fisher during agricultural research to measure complex interdependencies and interactions.