PSYB70H3 - Unit 6

Experiment

A study designed to determine causal relationships between variables.

Independent Variable (IV)

The variable manipulated by researchers.

Dependent Variable (DV)

The outcome variable that is measured.

Conditions

Different levels of the independent variable (e.g., number of witnesses in Darley and Latané's study).

Active Intervention

Researchers actively change the level of the IV (e.g., trauma vs. neutral writing).

Importance of Manipulation

Essential to eliminate alternative explanations for observed effects.

Single-Factor Two-Level Design

Experiments can have two levels.

Single-Factor Multi-Level Design

Experiments can have more than two levels.

Extraneous Variables

Variables other than IV and DV that can influence results (e.g., participant characteristics, situational factors).

Holding Variables Constant

(e.g., same location, instructions).

Limiting Participant Characteristics

To reduce variability.

Noise

Extraneous variables can introduce variability, making it difficult to identify the IV's effect.

Confounding Variables

Confounding variables vary systematically with the IV and can offer alternative explanations for results.

Treatment

Interventions aimed at changing behavior (e.g., therapy).

Control Condition

Participants do not receive the treatment, providing a baseline for comparison.

Placebo Effects

Non-active treatments that can still lead to perceived improvements based on expectations.

Between-Subjects Experiments

Each participant experiences only one condition.

Within-Subjects Experiments

Each participant experiences all conditions.

Random Assignment

A method to assign participants to conditions randomly, ensuring each participant has an equal chance of being in any condition.

Carryover Effects

When previous conditions affect participants' behavior in later conditions.

Practice Effect

Improved performance due to practice.

Fatigue Effect

Decreased performance due to tiredness.

Context Effect

Changes in perception based on prior conditions.

Counterbalancing

A technique used to control for order effects by varying the order of conditions across participants.

Complete Counterbalancing

Every possible order is tested.

Latin Square Design

Ensures each condition appears in every position and precedes and follows every other condition once.

Internal Validity

Degree to which an experiment supports a causal relationship between IV and DV.

External Validity

Degree to which study results can be generalized to other people and situations.

Construct Validity

Quality of the experiment's manipulations and operational definitions.

Statistical Validity

Proper statistical treatment of data and soundness of statistical conclusions.

Correlation vs. Causation

Just because two variables are related does not imply one causes the other.

Operationalization

Translating research questions into measurable variables.

Power Analysis

Calculation to determine the required sample size for detecting effects.

Quasi-Experimental Research

Involves manipulating an independent variable without random assignment to groups.

One-Group Quasi-Experimental Design

Design assessing treatment impact without control groups.

One-Group Posttest Only Design

Measures dependent variable after treatment application.

One-Group Pretest-Posttest Design

The dependent variable is measured before and after the treatment.

Interrupted Time Series Design

Multiple measurements taken over time around treatment.

Control Groups

Groups not receiving treatment for comparison.

Posttest Only Non-Equivalent Groups Design

Participants in one group receive a treatment, while a nonequivalent group does not.

Pretest-Posttest Non-Equivalent Groups Design

Participants are assessed before and after a treatment in both a treatment and a control group.

Interrupted Time-Series Design with Nonequivalent Groups

Measurements are taken at multiple intervals before and after an intervention for both a treatment group and a nonequivalent control group.

Pretest-Posttest Design with Switching Replication

Groups receive pretests, followed by an intervention for one group, and later switching the intervention for the second group.

Generalizability

Applicability of results to broader populations.

Treatment Condition

Participants receive intervention aimed at behavior change.

Threats to Internal Validity

Factors that can lead to incorrect conclusions.

Maturation Effects

Changes in participants over time affecting results.

Instrumentation

Changes in measurement tools affecting results.

Regression to the Mean

Extreme scores tend to move closer to average.

Spontaneous Remission

Natural improvement without treatment intervention.

Random Counterbalancing

Randomly assigns order of conditions for each participant.

Recruiting Participants

Identify target population early and plan recruitment strategies.

Formal Subject Pool

Participants from established groups.

Advertisements

Use ads or personal appeals to specific groups.

Volunteer Characteristics

Volunteers may differ from non-volunteers, affecting external validity.

Need for Standardization

Minimize extraneous variables during experimentation.

Written Protocol

Document all procedures and instructions.

Standard Instructions

Provide consistent instructions for all participants.

Automation

Use software to deliver parts of the procedure.

Anticipate Questions

Prepare answers for potential participant inquiries.

Training

Train experimenters uniformly.

Blind Experimenters

Limit knowledge of conditions to reduce expectancy effects.

Importance of Good Records

Maintain a sequence of conditions and participant demographics.

Confidentiality

Use identification numbers instead of names for participant data.

Manipulation Check

Measure to verify the successful manipulation of the independent variable.