Research Methods: Conducting Experiments and Factorial Designs

Flashcards covering lecture notes on measuring dependent variables, experimental pitfalls, and the foundation of factorial designs.

Sensitivity (DV)

The ability to detect differences in the Dependent Variable ($DV$), often improved through appropriate rating scales and avoiding ceiling or floor effects.

Ceiling effect

A problem where Dependent Variable ($DV$) scores are clustered at the high end, making it difficult to detect increases or differences.

Floor effect

A problem where Dependent Variable ($DV$) scores are clustered at the low end, making it difficult to detect decreases or differences.

Demand characteristics

Features of an experiment that indicate to participants what the researcher is looking for or what they want to find.

Experimenter bias (expectancy effects)

A pitfall where the researcher's expectations bias the results, as seen in the "Bloomers" study (Rosenthal & Jacobson, 1968) and the "Bright" and "dull" rats study (Rosenthal, 1966).

Double-blind study

A solution to experimenter bias where neither the participant nor the experimenter knows which condition the participant is in.

Pilot study

A small-scale trial run conducted before the main experiment to test procedures and materials.

Manipulation check

An assessment used to determine if the Independent Variable ($IV$) manipulation had the intended effect on participants.

Debriefing

The process of explaining the true nature of the study to participants after the experiment is completed.

Factorial Design

A design with 2 or more Independent Variables ($IVs$) where all levels of each $IV$ are crossed with all levels of each other $IV$.

2x2 Factorial Design

The simplest factorial design, featuring 2 Independent Variables with 2 levels each.

Mixed design

An experimental design that includes both between-subjects factors and within-subjects factors.

Interaction

A result in a factorial design where the effect of one Independent Variable ($IV$) differs based on the level of another Independent Variable ($IV$).

Main effect

The effect of a single Independent Variable ($IV$) alone, ignoring or averaging across the other Independent Variables ($IVs$).

Simple main effect

The effect of one Independent Variable ($IV$) at a specific, individual level of another Independent Variable ($IV$).