Psychological Research and Ethics Lectures

Vocabulary flashcards covering key terms in psychological research methods, ethics, sampling, statistics, and validity as discussed in Lectures #1–3.

Psychology

The scientific study of the mind, brain, and behavior.

Scientific Method

A systematic process of observation, hypothesis, experimentation, and conclusion used to generate knowledge.

Purpose (Principle of Psychological Science)

Clarifying why a study is being done by conceptualizing and operationalizing an idea, theory, or question.

Empiricism

Gathering objective evidence through standardized observation and measurement.

Results (Principle of Psychological Science)

Collecting data and drawing conclusions while acknowledging potential subjectivity in interpretation.

Transparency

Openly sharing methods, data, and peer-review processes to improve replicability and trust.

Confound

An uncontrolled variable that offers an alternative explanation for study results.

WEIRD Population

Samples that are Western, Educated, Industrialized, Rich, and Democratic—overrepresented in psychology research.

Replication Crisis

The 2012 revelation that many classic findings failed to reproduce, questioning reliability.

Publication Bias

Journals’ preference for significant, positive findings, leading to a skewed literature.

Producer of Research

Someone who plans, conducts, and publishes scientific studies (e.g., professors).

Consumer of Research

Someone who reads, evaluates, and applies research findings (e.g., students).

Basic Research

Research aimed at expanding fundamental knowledge without immediate application.

Translational Research

Work that bridges basic findings to potential practical uses or interventions.

Applied Research

Research directly testing solutions in real-world settings or populations.

Research Ethics Board (REB)

An institutional committee that reviews and monitors studies involving human participants.

Belmont Report

1979 U.S. document outlining ethical principles for human research: welfare, respect, and justice.

Concern for Welfare

Ethical duty to maximize benefits and minimize harms to participants.

Beneficence

Promoting benefits in research.

Non-maleficence

Avoiding or reducing harm to participants.

Respect for Persons

Honoring participants’ autonomy and protecting those with diminished capacity.

Informed Consent

Participants’ voluntary agreement after being fully informed of risks and benefits.

Justice (Ethical Principle)

Fair distribution of research burdens and benefits among groups.

Equity vs Equality

Providing resources based on need (equity) rather than identical treatment (equality).

Privacy

An individual’s right to control personal information shared with researchers.

Confidentiality

Researcher’s obligation to protect participants’ identifiable data.

Anonymity

Condition where even researchers cannot link data to individual identities.

Integrity (Ethical Principle)

Being accurate, truthful, and honest in conducting and reporting research.

Responsibility (Ethical Principle)

Adhering to societal laws and professional standards to maintain public trust.

Coercion

Using pressure or threats to compel participation.

Undue Influence

Offering excessive rewards or approval that improperly sway participation decisions.

Minimal Risk

Risk no greater than encountered in daily life; benchmark for ethical review.

Deception through Omission

Withholding information about a study’s true purpose.

Deception through Commission

Actively providing false information to participants about a study.

Assent

Agreement from minors or those lacking full capacity, complemented by guardian consent.

Safeguards

Procedures put in place to reduce or manage research risks.

Pre-registration

Publicly documenting hypotheses and methods before data collection to curb bias.

HARKing

Hypothesizing After Results are Known—post-hoc aligning hypotheses with outcomes.

Frequency Claim

A statement about the rate or proportion of something in a population.

Association Claim

A statement that two variables covary but no causality is asserted.

Causal Claim

A statement that one variable directly influences another.

Construct

An abstract concept (e.g., intelligence) researchers intend to measure.

Variable

A concrete, measurable representation of a construct.

Independent Variable (IV)

The variable manipulated to observe its effect.

Dependent Variable (DV)

The variable measured to assess the impact of the IV.

Covariance

Statistical relationship showing that changes in one variable correspond with changes in another.

Temporal Precedence

Requirement that the cause occurs before the effect in time.

Internal Validity

Degree to which a study establishes a trustworthy cause-and-effect relationship.

External Validity

Extent to which findings generalize beyond the study sample and settings.

Construct Validity

Accuracy with which variables represent the underlying constructs.

Statistical Validity

Appropriateness and accuracy of the data analyses and resulting conclusions.

Population Validity

Subtype of external validity assessing how well a sample represents the target population.

Ecological Validity

Extent to which study conditions resemble real-world environments.

Experiential Realism

The degree to which participants find the experimental situation engaging and realistic.

Direct Replication

Repeating a study’s procedures closely to verify results.

Conceptual Replication

Testing the same hypothesis with different methods or measures.

Probability Sampling

Selecting participants using random, unbiased methods so each population member has a known chance.

Simple Random Sample

Every population member has an equal probability of selection via random process.

Cluster Sample

Randomly selecting whole groups (clusters) and including all members within them.

Multi-stage Cluster Sample

Randomly selecting clusters, then randomly sampling individuals within those clusters.

Stratified Sample

Sampling within demographic strata to ensure representation.

Proportionate Stratified Sampling

Selecting participants from strata in proportion to their population size.

Disproportionate Stratified Sampling

Oversampling smaller strata to achieve equal subgroup sizes.

Non-probability Sampling

Sampling methods lacking random selection, increasing bias risk.

Convenience Sample

Participants selected because they are easily available.

Purposive Sample

Intentionally recruiting individuals with specific characteristics relevant to the study.

Snowball Sample

Current participants recruit acquaintances into the study.

Quota Sample

Recruiting until preset numbers for each subgroup are met without random selection.

Random Assignment

Randomly placing sampled participants into experimental conditions to equalize groups.

Central Tendency

Measures (mean, median, mode) that summarize the center of a data distribution.

Mean

Arithmetic average of a set of scores.

Median

Middle score when data are ordered from lowest to highest.

Mode

Most frequently occurring score in a dataset.

Standard Deviation

Average distance of scores from the mean; indicates variability.

Variance

Squared standard deviation; mathematically useful measure of spread.

Skew (Right/Positive)

Distribution with a tail extending toward higher values.

Skew (Left/Negative)

Distribution with a tail extending toward lower values.

Bimodal Distribution

Data pattern showing two distinct peaks.

Uniform Distribution

Each value occurs with roughly equal frequency across the range.

Point Estimate

A single sample statistic (e.g., 54%) used to infer a population parameter.

Margin of Error

Range around a point estimate likely to contain the true population value.

Confidence Interval

Interval within which the population parameter falls with a specified probability (e.g., 95%).

Sample Size

Number of observations in a study; larger sizes reduce margin of error.

Null Hypothesis

Assumption that there is no effect or difference until evidence suggests otherwise.

Comparison Group

Any group to which another group’s outcomes are contrasted in a study.

Control Group

A comparison group receiving no experimental manipulation, serving as a baseline.

Alternative Explanations

Other variables that could account for observed relationships; threats to validity.