Sampling Methods and Generalizability (Random Sampling vs. Random Assignment)

Vocabulary flashcards covering key sampling concepts, methods, and generalizability from the lecture notes.

Random Sampling

A sampling method where every member of the population has an equal chance of being selected, increasing the generalizability of findings.

Random Assignment

Assigning participants to experimental and control groups after recruitment; enhances internal validity and enables cause‑and‑effect conclusions.

Sampling Bias

A bias that occurs when the sample does not accurately represent the population of interest.

Volunteer Bias

Bias that arises when only motivated individuals volunteer to participate in a study.

Convenience Bias

Bias from using an easily accessible sample, which typically limits generalizability.

Systematic Sampling

A sampling method that selects every nth person from a list; quick and easy, but can introduce bias if there is a hidden pattern in the list.

Stratified Sampling

A sampling method that divides the population into subgroups (strata) based on characteristics and samples proportionally from each group to ensure representation of important subgroups.

Cluster Sampling

Divide the population into clusters (e.g., classrooms or neighborhoods), randomly select some clusters, and survey all individuals within those clusters; efficient when the population is spread out.

Generalizability

The extent to which study findings apply to the larger population; high when samples are random and representative, low when samples are biased, small, or convenience-based.

Case Studies

In-depth investigations of a single case or a small number of cases; detailed but not typically generalizable.

Correlational Studies

Research designs that examine relationships between variables but do not establish causation.

Internal Validity

The extent to which a study demonstrates a causal relationship by ruling out confounding variables; enhanced by random assignment.

Random Sampling

A sampling method where every member of the population has an equal chance of being selected, increasing the generalizability of findings.

Random Assignment

Assigning participants to experimental and control groups after recruitment; enhances internal validity and enables cause‑and‑effect conclusions.

Sampling Bias

A bias that occurs when the sample does not accurately represent the population of interest.

Volunteer Bias

Bias that arises when only motivated individuals volunteer to participate in a study.

Convenience Bias

Bias from using an easily accessible sample, which typically limits generalizability.

Systematic Sampling

A sampling method that selects every nth person from a list; quick and easy, but can introduce bias if there is a hidden pattern in the list.

Stratified Sampling

A sampling method that divides the population into subgroups (strata) based on characteristics and samples proportionally from each group to ensure representation of important subgroups.

Cluster Sampling

Divide the population into clusters (e.g., classrooms or neighborhoods), randomly select some clusters, and survey all individuals within those clusters; efficient when the population is spread out.

Generalizability

The extent to which study findings apply to the larger population; high when samples are random and representative, low when samples are biased, small, or convenience-based.

Case Studies

In-depth investigations of a single case or a small number of cases; detailed but not typically generalizable.

Correlational Studies

Research designs that examine relationships between variables but do not establish causation.

Internal Validity

The extent to which a study demonstrates a causal relationship by ruling out confounding variables; enhanced by random assignment.

Independent Variable (IV)

The variable that is manipulated by the researcher in an experiment to observe its effect on an outcome variable.

Dependent Variable (DV)

The variable that is measured in an experiment and is expected to change as a result of the independent variable manipulation.

Confounding Variable

An unmeasured variable that influences both the independent and dependent variables, potentially leading to a spurious relationship.

Experimental Group

The group in an experiment that receives the treatment or manipulation of the independent variable.

Control Group

The group in an experiment that does not receive the treatment, serving as a baseline for comparison with the experimental group.

Reliability

The consistency of a measure; a reliable measure produces similar results under the same conditions.

External Validity

The extent to which the findings of a study can be generalized to other populations, settings, and times.

Construct Validity

The degree to which a test or measure accurately assesses the underlying construct or concept it is intended to measure.

Informed Consent

The ethical principle requiring researchers to fully inform participants about the study's nature, risks, and benefits before they agree to participate.

Debriefing

The process of informing participants about the true nature of a study and any deception used, after the study has concluded.

Placebo Effect

A psychological or physiological effect observed in participants due to their belief in the treatment, rather than the treatment itself.

Observational Studies

Research designs where the researcher observes and systematically records behavior without manipulating any variables; can describe relationships but not establish causation.

Quasi-Experimental Design

Research designs that resemble experimental studies but lack random assignment to groups, often using pre-existing groups or natural events.