Set 6: Research + Academic Sociology Language

Research Method

A systematic strategy used to collect and analyze evidence about social life. THINK: How are we going to study this?

Methodology

The broader logic, assumptions, and rationale underlying how research is designed and conducted. THINK: Why this research approach makes sense. NOT simply: The specific method itself.

Method vs. Methodology

METHOD = the technique used to collect or analyze data; METHODOLOGY = the reasoning and framework behind those choices.

Empirical

Based on systematic observation or evidence. THINK: What does the evidence show?

Theoretical

Related to concepts, propositions, or explanatory frameworks used to interpret social patterns. THINK: How are we explaining what the evidence means?

Empirical vs. Theoretical

EMPIRICAL concerns observed evidence; THEORETICAL concerns the concepts and explanations used to interpret that evidence.

Research Question

The specific question a study is designed to answer. THINK: What exactly are we trying to find out?

Hypothesis

A testable prediction about the relationship between variables. THINK: What do we expect to find?

Theory

An organized explanation of how and why social phenomena occur. THINK: Broader explanation.

Hypothesis vs. Theory

A HYPOTHESIS is a specific testable prediction; a THEORY is a broader explanatory framework that may generate many hypotheses.

Concept

An abstract idea used to describe or analyze social reality. EXAMPLES: prejudice, class, power, social cohesion.

Variable

A characteristic or condition that can take different values across people, groups, places, or time. EXAMPLES: age, income, education, prejudice level.

Concept vs. Variable

A CONCEPT is an abstract idea; a VARIABLE is a measurable form that can vary. THINK: Idea vs. measurable variation.

Operationalization

The process of specifying how an abstract concept will be measured or observed in a study. THINK: How do I turn "social trust" into something I can actually measure?

Operational Definition

The specific way a researcher defines and measures a concept for a particular study.

Conceptual Definition

The theoretical meaning of a concept. THINK: What does this idea mean?

Conceptual vs. Operational Definition

CONCEPTUAL definition explains what a concept means; OPERATIONAL definition explains how it will be measured.

Indicator

A specific observable measure used to represent a broader concept. EXAMPLE: Years of education as an indicator of educational attainment.

Measurement

The process of assigning values or categories to concepts in a systematic way.

Level of Measurement

The type of information contained in a variable and what comparisons are meaningful. Common levels: nominal, ordinal, interval, ratio.

Nominal Variable

A variable consisting of categories with no inherent ranking. EXAMPLES: marital status, religion category.

Ordinal Variable

A variable with categories that can be ranked but whose distances are not necessarily equal. EXAMPLES: strongly disagree to strongly agree.

Interval Variable

A numerical variable with equal intervals between values but no true zero. CLASSIC EXAMPLE: Celsius temperature.

Ratio Variable

A numerical variable with equal intervals and a meaningful zero. EXAMPLES: income, age, number of children.

Nominal vs. Ordinal

NOMINAL categories have no rank; ORDINAL categories have a meaningful order.

Interval vs. Ratio

Both have equal numerical intervals, but RATIO variables have a meaningful zero.

Independent Variable

A variable proposed to influence, predict, or explain another variable. THINK: Potential cause or predictor.

Dependent Variable

The outcome a researcher is trying to explain or predict. THINK: What changes?

Independent vs. Dependent Variable

INDEPENDENT = presumed predictor/cause; DEPENDENT = outcome being explained. THINK: X → Y.

Control Variable

A variable held constant or statistically accounted for so researchers can better isolate another relationship.

Confounding Variable

A factor related to both the presumed cause and outcome that can distort the apparent relationship between them. THINK: A hidden third factor may explain the pattern.

Confound vs. Control Variable

A CONFOUND is a third variable that may distort a relationship; a CONTROL VARIABLE is something researchers account for to reduce that distortion.

Extraneous Variable

A variable not central to the research question that may nonetheless influence the outcome.

Mediating Variable

A variable that helps explain HOW or WHY one variable affects another. THINK: X affects M, which affects Y.

Mediator

A mechanism or pathway connecting a predictor to an outcome. THINK: The middle step.

Moderating Variable

A variable that changes the strength or direction of a relationship between two other variables. THINK: X affects Y differently depending on Z.

Mediator vs. Moderator

MEDIATOR explains HOW X affects Y; MODERATOR explains WHEN, FOR WHOM, or UNDER WHAT CONDITIONS X affects Y.

Correlation

A statistical association between two variables. THINK: They vary together.

Positive Correlation

A relationship in which higher values of one variable are associated with higher values of another.

Negative Correlation

A relationship in which higher values of one variable are associated with lower values of another.

Zero Correlation

Little or no systematic relationship between two variables.

Correlation vs. Causation

CORRELATION means two variables are associated; CAUSATION means changes in one help produce changes in the other.

Causation

A relationship in which one factor contributes to producing change in another. Establishing causation generally requires evidence of association, temporal order, and elimination of plausible alternative explanations.

Temporal Order

The requirement that a cause must occur before its presumed effect. THINK: Cause first, outcome second.

Spurious Relationship

An apparent relationship between two variables that is actually produced by a third variable. THINK: X and Y look connected, but Z is driving both.

Causal Mechanism

The process through which one condition produces or contributes to another. THINK: What is the actual HOW connecting X to Y?

Association

A general relationship between variables or social phenomena. Association does not automatically imply causation.

Effect

The change in an outcome associated with or produced by another factor, depending on the research design and evidence.

Effect Size

A measure of how large or meaningful a relationship or difference is. THINK: Not just "is there an effect?" but "how big is it?"

Statistical Significance

A statistical judgment about whether an observed result would be unlikely under a specified null model. IMPORTANT: Statistical significance does NOT tell you whether the effect is large or socially important.

Practical Significance

The real-world importance or meaningfulness of a research finding. THINK: Does this difference actually matter?

Statistical vs. Practical Significance

STATISTICAL significance asks whether the result is unlikely to be due to sampling variation under the null model; PRACTICAL significance asks whether the effect is meaningful in the real world.

Population

The entire group a researcher wants to understand or make claims about.

Sample

A subset of a population selected for study.

Population vs. Sample

POPULATION = everyone of interest; SAMPLE = the people actually studied.

Sampling

The process of selecting cases from a population for research.

Sampling Frame

The list or source from which a sample is actually drawn. THINK: Who had a chance to be selected?

Representative Sample

A sample that resembles the population on relevant characteristics closely enough to support appropriate generalization.

Probability Sampling

A sampling approach in which members of the population have a known chance of selection.

Random Sample

A probability sample in which selection is determined through random procedures, reducing systematic selection bias.

Simple Random Sample

A sample in which each member of the population has an equal chance of selection.

Stratified Sample

A probability sample created by dividing a population into subgroups and sampling from each. THINK: Ensure important categories are represented.

Cluster Sample

A probability sample created by randomly selecting groups or clusters first, then studying people within those clusters.

Systematic Sample

A sample selected by choosing every nth case from an ordered list after a random starting point.

Nonprobability Sampling

A sampling approach in which cases do not have known or equal probabilities of selection.

Convenience Sample

A sample selected because participants are easy to access. THINK: Easy, but potentially biased.

Purposive Sample

A nonprobability sample in which researchers deliberately select cases with characteristics especially relevant to the research question.

Snowball Sampling

A sampling method in which existing participants recruit or refer additional participants. Useful for hard-to-reach populations.

Sampling Bias

Systematic distortion caused when some members of a population are more likely than others to be included in a sample.

Selection Bias

Systematic differences between people who enter a study or group and those who do not, potentially distorting results.

Nonresponse Bias

Bias that occurs when people who do not participate differ meaningfully from those who do.

Generalizability

The extent to which findings from a study can reasonably be applied to a broader population or setting.

External Validity

The degree to which study findings generalize beyond the specific sample, setting, or conditions studied.

Internal Validity

The degree to which a study supports a credible conclusion that the presumed cause actually produced the observed outcome.

Internal vs. External Validity

INTERNAL validity asks whether the causal conclusion is credible within the study; EXTERNAL validity asks whether findings generalize beyond the study.

Validity

The extent to which a measure or study accurately captures what it is intended to capture.

Reliability

The consistency or stability of a measurement or research procedure.

Validity vs. Reliability

RELIABILITY means consistent; VALIDITY means accurate. A measure can be reliable without being valid.

Construct Validity

The degree to which a measure accurately represents the theoretical concept it is supposed to measure.

Content Validity

The extent to which a measure adequately covers the full range of a concept.

Criterion Validity

The extent to which a measure corresponds with another accepted indicator or relevant outcome.

Face Validity

The degree to which a measure appears, on the surface, to measure what it claims to measure.

Measurement Error

Difference between the true value of a characteristic and the value produced by a measurement process.

Random Error

Measurement error that varies unpredictably and tends to reduce precision.

Systematic Error

Measurement error that consistently pushes results in a particular direction. THINK: Built-in bias.

Bias

A systematic tendency that distorts research findings away from an accurate representation.

Researcher Bias

Ways a researcher's expectations, assumptions, or behavior may systematically influence data collection or interpretation.

Confirmation Bias

The tendency to notice or favor evidence that supports existing expectations while discounting contradictory evidence.

Observer Effect

Change in participants' behavior because they know they are being observed.

Hawthorne Effect

A proposed form of observer effect in which people modify behavior because they know they are participating in a study.

Social Desirability Bias

The tendency for participants to give answers they believe are socially acceptable rather than fully accurate.

Recall Bias

Error caused by participants remembering past experiences inaccurately or differently across groups.

Question-Wording Effect

Changes in responses caused by how survey questions are phrased.

Leading Question

A question phrased in a way that encourages a particular answer.

Double-Barreled Question

A survey question that asks about two or more things at once, making responses difficult to interpret.

Survey

A research method that systematically collects self-reported information from participants, often through questionnaires or interviews.

Questionnaire

A standardized set of written or digital questions used to collect data.

Interview

A research method involving direct questioning of participants, which may be structured, semi-structured, or unstructured.

Structured Interview

An interview using standardized questions asked in the same way across participants.

Semi-Structured Interview

An interview guided by prepared questions while allowing flexibility for follow-up and exploration.