key terms in research

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Glossary of research terms.

• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Resources
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

This glossary is intended to assist you in understanding commonly used terms and concepts when reading, interpreting, and evaluating scholarly research. Also included are common words and phrases defined within the context of how they apply to research in the social and behavioral sciences. Definitions have been adapted from the sources cited below.

• Acculturation -- refers to the process of adapting to another culture, particularly in reference to blending in with the majority population [e.g., an immigrant adopting American customs]. However, acculturation also implies that both cultures add something to one another, but still remain distinct groups unto themselves.
• Accuracy -- a term used in survey research to refer to the match between the target population and the sample.
• Affective Measures -- procedures or devices used to obtain quantified descriptions of an individual's feelings, emotional states, or dispositions.
• Aggregate -- a total created from smaller units. For instance, the population of a county is an aggregate of the populations of the cities, rural areas, etc. that comprise the county. As a verb, it refers to total data from smaller units into a large unit.
• Anonymity -- a research condition in which no one, including the researcher, knows the identities of research participants.
• Baseline -- a control measurement carried out before an experimental treatment.
• Behaviorism -- school of psychological thought concerned with the observable, tangible, objective facts of behavior, rather than with subjective phenomena such as thoughts, emotions, or impulses. Contemporary behaviorism also emphasizes the study of mental states such as feelings and fantasies to the extent that they can be directly observed and measured.
• Beliefs -- ideas, doctrines, tenets, etc. that are accepted as true on grounds which are not immediately susceptible to rigorous proof.
• Benchmarking -- systematically measuring and comparing the operations and outcomes of organizations, systems, processes, etc., against agreed upon "best-in-class" frames of reference.
• Bias -- a loss of balance and accuracy in the use of research methods. It can appear in research via the sampling frame, random sampling, or non-response. It can also occur at other stages in research, such as while interviewing, in the design of questions, or in the way data are analyzed and presented. Bias means that the research findings will not be representative of, or generalizable to, a wider population.
• Case Study -- the collection and presentation of detailed information about a particular participant or small group, frequently including data derived from the subjects themselves.
• Causal Hypothesis -- a statement hypothesizing that the independent variable affects the dependent variable in some way.
• Causal Relationship -- the relationship established that shows that an independent variable, and nothing else, causes a change in a dependent variable. It also establishes how much of a change is shown in the dependent variable.
• Causality -- the relation between cause and effect.
• Central Tendency -- any way of describing or characterizing typical, average, or common values in some distribution.
• Chi-square Analysis -- a common non-parametric statistical test which compares an expected proportion or ratio to an actual proportion or ratio.
• Claim -- a statement, similar to a hypothesis, which is made in response to the research question and that is affirmed with evidence based on research.
• Classification -- ordering of related phenomena into categories, groups, or systems according to characteristics or attributes.
• Cluster Analysis -- a method of statistical analysis where data that share a common trait are grouped together. The data is collected in a way that allows the data collector to group data according to certain characteristics.
• Cohort Analysis -- group by group analytic treatment of individuals having a statistical factor in common to each group. Group members share a particular characteristic [e.g., born in a given year] or a common experience [e.g., entering a college at a given time].
• Confidentiality -- a research condition in which no one except the researcher(s) knows the identities of the participants in a study. It refers to the treatment of information that a participant has disclosed to the researcher in a relationship of trust and with the expectation that it will not be revealed to others in ways that violate the original consent agreement, unless permission is granted by the participant.
• Confirmability Objectivity -- the findings of the study could be confirmed by another person conducting the same study.
• Construct -- refers to any of the following: something that exists theoretically but is not directly observable; a concept developed [constructed] for describing relations among phenomena or for other research purposes; or, a theoretical definition in which concepts are defined in terms of other concepts. For example, intelligence cannot be directly observed or measured; it is a construct.
• Construct Validity -- seeks an agreement between a theoretical concept and a specific measuring device, such as observation.
• Constructivism -- the idea that reality is socially constructed. It is the view that reality cannot be understood outside of the way humans interact and that the idea that knowledge is constructed, not discovered. Constructivists believe that learning is more active and self-directed than either behaviorism or cognitive theory would postulate.
• Content Analysis -- the systematic, objective, and quantitative description of the manifest or latent content of print or nonprint communications.
• Context Sensitivity -- awareness by a qualitative researcher of factors such as values and beliefs that influence cultural behaviors.
• Control Group -- the group in an experimental design that receives either no treatment or a different treatment from the experimental group. This group can thus be compared to the experimental group.
• Controlled Experiment -- an experimental design with two or more randomly selected groups [an experimental group and control group] in which the researcher controls or introduces the independent variable and measures the dependent variable at least two times [pre- and post-test measurements].
• Correlation -- a common statistical analysis, usually abbreviated as r, that measures the degree of relationship between pairs of interval variables in a sample. The range of correlation is from -1.00 to zero to +1.00. Also, a non-cause and effect relationship between two variables.
• Covariate -- a product of the correlation of two related variables times their standard deviations. Used in true experiments to measure the difference of treatment between them.
• Credibility -- a researcher's ability to demonstrate that the object of a study is accurately identified and described based on the way in which the study was conducted.
• Critical Theory -- an evaluative approach to social science research, associated with Germany's neo-Marxist “Frankfurt School,” that aims to criticize as well as analyze society, opposing the political orthodoxy of modern communism. Its goal is to promote human emancipatory forces and to expose ideas and systems that impede them.
• Data -- factual information [as measurements or statistics] used as a basis for reasoning, discussion, or calculation.
• Data Mining -- the process of analyzing data from different perspectives and summarizing it into useful information, often to discover patterns and/or systematic relationships among variables.
• Data Quality -- this is the degree to which the collected data [results of measurement or observation] meet the standards of quality to be considered valid [trustworthy] and  reliable [dependable].
• Deductive -- a form of reasoning in which conclusions are formulated about particulars from general or universal premises.
• Dependability -- being able to account for changes in the design of the study and the changing conditions surrounding what was studied.
• Dependent Variable -- a variable that varies due, at least in part, to the impact of the independent variable. In other words, its value “depends” on the value of the independent variable. For example, in the variables “gender” and “academic major,” academic major is the dependent variable, meaning that your major cannot determine whether you are male or female, but your gender might indirectly lead you to favor one major over another.
• Deviation -- the distance between the mean and a particular data point in a given distribution.
• Discourse Community -- a community of scholars and researchers in a given field who respond to and communicate to each other through published articles in the community's journals and presentations at conventions. All members of the discourse community adhere to certain conventions for the presentation of their theories and research.
• Discrete Variable -- a variable that is measured solely in whole units, such as, gender and number of siblings.
• Distribution -- the range of values of a particular variable.
• Effect Size -- the amount of change in a dependent variable that can be attributed to manipulations of the independent variable. A large effect size exists when the value of the dependent variable is strongly influenced by the independent variable. It is the mean difference on a variable between experimental and control groups divided by the standard deviation on that variable of the pooled groups or of the control group alone.
• Emancipatory Research -- research is conducted on and with people from marginalized groups or communities. It is led by a researcher or research team who is either an indigenous or external insider; is interpreted within intellectual frameworks of that group; and, is conducted largely for the purpose of empowering members of that community and improving services for them. It also engages members of the community as co-constructors or validators of knowledge.
• Empirical Research -- the process of developing systematized knowledge gained from observations that are formulated to support insights and generalizations about the phenomena being researched.
• Epistemology -- concerns knowledge construction; asks what constitutes knowledge and how knowledge is validated.
• Ethnography -- method to study groups and/or cultures over a period of time. The goal of this type of research is to comprehend the particular group/culture through immersion into the culture or group. Research is completed through various methods but, since the researcher is immersed within the group for an extended period of time, more detailed information is usually collected during the research.
• Expectancy Effect -- any unconscious or conscious cues that convey to the participant in a study how the researcher wants them to respond. Expecting someone to behave in a particular way has been shown to promote the expected behavior. Expectancy effects can be minimized by using standardized interactions with subjects, automated data-gathering methods, and double blind protocols.
• External Validity -- the extent to which the results of a study are generalizable or transferable.
• Factor Analysis -- a statistical test that explores relationships among data. The test explores which variables in a data set are most related to each other. In a carefully constructed survey, for example, factor analysis can yield information on patterns of responses, not simply data on a single response. Larger tendencies may then be interpreted, indicating behavior trends rather than simply responses to specific questions.
• Field Studies -- academic or other investigative studies undertaken in a natural setting, rather than in laboratories, classrooms, or other structured environments.
• Focus Groups -- small, roundtable discussion groups charged with examining specific topics or problems, including possible options or solutions. Focus groups usually consist of 4-12 participants, guided by moderators to keep the discussion flowing and to collect and report the results.
• Framework -- the structure and support that may be used as both the launching point and the on-going guidelines for investigating a research problem.
• Generalizability -- the extent to which research findings and conclusions conducted on a specific study to groups or situations can be applied to the population at large.
• Grey Literature -- research produced by organizations outside of commercial and academic publishing that publish materials, such as, working papers, research reports, and briefing papers.
• Grounded Theory -- practice of developing other theories that emerge from observing a group. Theories are grounded in the group's observable experiences, but researchers add their own insight into why those experiences exist.
• Group Behavior -- behaviors of a group as a whole, as well as the behavior of an individual as influenced by his or her membership in a group.
• Hypothesis -- a tentative explanation based on theory to predict a causal relationship between variables.
• Independent Variable -- the conditions of an experiment that are systematically manipulated by the researcher. A variable that is not impacted by the dependent variable, and that itself impacts the dependent variable. In the earlier example of "gender" and "academic major," (see Dependent Variable) gender is the independent variable.
• Individualism -- a theory or policy having primary regard for the liberty, rights, or independent actions of individuals.
• Inductive -- a form of reasoning in which a generalized conclusion is formulated from particular instances.
• Inductive Analysis -- a form of analysis based on inductive reasoning; a researcher using inductive analysis starts with answers, but formulates questions throughout the research process.
• Insiderness -- a concept in qualitative research that refers to the degree to which a researcher has access to and an understanding of persons, places, or things within a group or community based on being a member of that group or community.
• Internal Consistency -- the extent to which all questions or items assess the same characteristic, skill, or quality.
• Internal Validity -- the rigor with which the study was conducted [e.g., the study's design, the care taken to conduct measurements, and decisions concerning what was and was not measured]. It is also the extent to which the designers of a study have taken into account alternative explanations for any causal relationships they explore. In studies that do not explore causal relationships, only the first of these definitions should be considered when assessing internal validity.
• Life History -- a record of an event/events in a respondent's life told [written down, but increasingly audio or video recorded] by the respondent from his/her own perspective in his/her own words. A life history is different from a "research story" in that it covers a longer time span, perhaps a complete life, or a significant period in a life.
• Margin of Error -- the permittable or acceptable deviation from the target or a specific value. The allowance for slight error or miscalculation or changing circumstances in a study.
• Measurement -- process of obtaining a numerical description of the extent to which persons, organizations, or things possess specified characteristics.
• Meta-Analysis -- an analysis combining the results of several studies that address a set of related hypotheses.
• Methodology -- a theory or analysis of how research does and should proceed.
• Methods -- systematic approaches to the conduct of an operation or process. It includes steps of procedure, application of techniques, systems of reasoning or analysis, and the modes of inquiry employed by a discipline.
• Mixed-Methods -- a research approach that uses two or more methods from both the quantitative and qualitative research categories. It is also referred to as blended methods, combined methods, or methodological triangulation.
• Modeling -- the creation of a physical or computer analogy to understand a particular phenomenon. Modeling helps in estimating the relative magnitude of various factors involved in a phenomenon. A successful model can be shown to account for unexpected behavior that has been observed, to predict certain behaviors, which can then be tested experimentally, and to demonstrate that a given theory cannot account for certain phenomenon.
• Models -- representations of objects, principles, processes, or ideas often used for imitation or emulation.
• Naturalistic Observation -- observation of behaviors and events in natural settings without experimental manipulation or other forms of interference.
• Norm -- the norm in statistics is the average or usual performance. For example, students usually complete their high school graduation requirements when they are 18 years old. Even though some students graduate when they are younger or older, the norm is that any given student will graduate when he or she is 18 years old.
• Null Hypothesis -- the proposition, to be tested statistically, that the experimental intervention has "no effect," meaning that the treatment and control groups will not differ as a result of the intervention. Investigators usually hope that the data will demonstrate some effect from the intervention, thus allowing the investigator to reject the null hypothesis.
• Ontology -- a discipline of philosophy that explores the science of what is, the kinds and structures of objects, properties, events, processes, and relations in every area of reality.
• Panel Study -- a longitudinal study in which a group of individuals is interviewed at intervals over a period of time.
• Participant -- individuals whose physiological and/or behavioral characteristics and responses are the object of study in a research project.
• Peer-Review -- the process in which the author of a book, article, or other type of publication submits his or her work to experts in the field for critical evaluation, usually prior to publication. This is standard procedure in publishing scholarly research.
• Phenomenology -- a qualitative research approach concerned with understanding certain group behaviors from that group's point of view.
• Philosophy -- critical examination of the grounds for fundamental beliefs and analysis of the basic concepts, doctrines, or practices that express such beliefs.
• Phonology -- the study of the ways in which speech sounds form systems and patterns in language.
• Policy -- governing principles that serve as guidelines or rules for decision making and action in a given area.
• Policy Analysis -- systematic study of the nature, rationale, cost, impact, effectiveness, implications, etc., of existing or alternative policies, using the theories and methodologies of relevant social science disciplines.
• Population -- the target group under investigation. The population is the entire set under consideration. Samples are drawn from populations.
• Position Papers -- statements of official or organizational viewpoints, often recommending a particular course of action or response to a situation.
• Positivism -- a doctrine in the philosophy of science, positivism argues that science can only deal with observable entities known directly to experience. The positivist aims to construct general laws, or theories, which express relationships between phenomena. Observation and experiment is used to show whether the phenomena fit the theory.
• Predictive Measurement -- use of tests, inventories, or other measures to determine or estimate future events, conditions, outcomes, or trends.
• Principal Investigator -- the scientist or scholar with primary responsibility for the design and conduct of a research project.
• Probability -- the chance that a phenomenon will occur randomly. As a statistical measure, it is shown as p [the "p" factor].
• Questionnaire -- structured sets of questions on specified subjects that are used to gather information, attitudes, or opinions.
• Random Sampling -- a process used in research to draw a sample of a population strictly by chance, yielding no discernible pattern beyond chance. Random sampling can be accomplished by first numbering the population, then selecting the sample according to a table of random numbers or using a random-number computer generator. The sample is said to be random because there is no regular or discernible pattern or order. Random sample selection is used under the assumption that sufficiently large samples assigned randomly will exhibit a distribution comparable to that of the population from which the sample is drawn. The random assignment of participants increases the probability that differences observed between participant groups are the result of the experimental intervention.
• Reliability -- the degree to which a measure yields consistent results. If the measuring instrument [e.g., survey] is reliable, then administering it to similar groups would yield similar results. Reliability is a prerequisite for validity. An unreliable indicator cannot produce trustworthy results.
• Representative Sample -- sample in which the participants closely match the characteristics of the population, and thus, all segments of the population are represented in the sample. A representative sample allows results to be generalized from the sample to the population.
• Rigor -- degree to which research methods are scrupulously and meticulously carried out in order to recognize important influences occurring in an experimental study.
• Sample -- the population researched in a particular study. Usually, attempts are made to select a "sample population" that is considered representative of groups of people to whom results will be generalized or transferred. In studies that use inferential statistics to analyze results or which are designed to be generalizable, sample size is critical, generally the larger the number in the sample, the higher the likelihood of a representative distribution of the population.
• Sampling Error -- the degree to which the results from the sample deviate from those that would be obtained from the entire population, because of random error in the selection of respondent and the corresponding reduction in reliability.
• Saturation -- a situation in which data analysis begins to reveal repetition and redundancy and when new data tend to confirm existing findings rather than expand upon them.
• Semantics -- the relationship between symbols and meaning in a linguistic system. Also, the cuing system that connects what is written in the text to what is stored in the reader's prior knowledge.
• Social Theories -- theories about the structure, organization, and functioning of human societies.
• Sociolinguistics -- the study of language in society and, more specifically, the study of language varieties, their functions, and their speakers.
• Standard Deviation -- a measure of variation that indicates the typical distance between the scores of a distribution and the mean; it is determined by taking the square root of the average of the squared deviations in a given distribution. It can be used to indicate the proportion of data within certain ranges of scale values when the distribution conforms closely to the normal curve.
• Statistical Analysis -- application of statistical processes and theory to the compilation, presentation, discussion, and interpretation of numerical data.
• Statistical Bias -- characteristics of an experimental or sampling design, or the mathematical treatment of data, that systematically affects the results of a study so as to produce incorrect, unjustified, or inappropriate inferences or conclusions.
• Statistical Significance -- the probability that the difference between the outcomes of the control and experimental group are great enough that it is unlikely due solely to chance. The probability that the null hypothesis can be rejected at a predetermined significance level [0.05 or 0.01].
• Statistical Tests -- researchers use statistical tests to make quantitative decisions about whether a study's data indicate a significant effect from the intervention and allow the researcher to reject the null hypothesis. That is, statistical tests show whether the differences between the outcomes of the control and experimental groups are great enough to be statistically significant. If differences are found to be statistically significant, it means that the probability [likelihood] that these differences occurred solely due to chance is relatively low. Most researchers agree that a significance value of .05 or less [i.e., there is a 95% probability that the differences are real] sufficiently determines significance.
• Subcultures -- ethnic, regional, economic, or social groups exhibiting characteristic patterns of behavior sufficient to distinguish them from the larger society to which they belong.
• Testing -- the act of gathering and processing information about individuals' ability, skill, understanding, or knowledge under controlled conditions.
• Theory -- a general explanation about a specific behavior or set of events that is based on known principles and serves to organize related events in a meaningful way. A theory is not as specific as a hypothesis.
• Treatment -- the stimulus given to a dependent variable.
• Trend Samples -- method of sampling different groups of people at different points in time from the same population.
• Triangulation -- a multi-method or pluralistic approach, using different methods in order to focus on the research topic from different viewpoints and to produce a multi-faceted set of data. Also used to check the validity of findings from any one method.
• Unit of Analysis -- the basic observable entity or phenomenon being analyzed by a study and for which data are collected in the form of variables.
• Validity -- the degree to which a study accurately reflects or assesses the specific concept that the researcher is attempting to measure. A method can be reliable, consistently measuring the same thing, but not valid.
• Variable -- any characteristic or trait that can vary from one person to another [race, gender, academic major] or for one person over time [age, political beliefs].
• Weighted Scores -- scores in which the components are modified by different multipliers to reflect their relative importance.
• White Paper -- an authoritative report that often states the position or philosophy about a social, political, or other subject, or a general explanation of an architecture, framework, or product technology written by a group of researchers. A white paper seeks to contain unbiased information and analysis regarding a business or policy problem that the researchers may be facing.

Elliot, Mark, Fairweather, Ian, Olsen, Wendy Kay, and Pampaka, Maria. A Dictionary of Social Research Methods. Oxford, UK: Oxford University Press, 2016; Free Social Science Dictionary. Socialsciencedictionary.com [2008]. Glossary. Institutional Review Board. Colorado College; Glossary of Key Terms. Writing@CSU. Colorado State University; Glossary A-Z. Education.com; Glossary of Research Terms. Research Mindedness Virtual Learning Resource. Centre for Human Servive Technology. University of Southampton; Miller, Robert L. and Brewer, John D. The A-Z of Social Research: A Dictionary of Key Social Science Research Concepts London: SAGE, 2003; Jupp, Victor. The SAGE Dictionary of Social and Cultural Research Methods . London: Sage, 2006.

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Research Terms

Ai generator.

Research terms are specific words or phrases used in academic writing to describe the research process, methodologies, and findings. These include concepts like hypothesis , variables, sample size, literature review, and data analysis. Understanding these terms is crucial for interpreting research studies and effectively communicating ideas. Mastery of research terms enhances clarity in academic discourse, whether in a research project proposal , a qualitative research report , or the description of research methodology.

What are terms in research?

Terms in research refer to the specific words, phrases, and concepts used within a study to define its scope, methodology , and focus. These terms ensure clarity and precision, allowing researchers to communicate ideas and findings effectively. Clear definitions facilitate a shared understanding and maintain the integrity and replicability of research.

Examples of Research Terms

• Hypothesis : A proposed explanation for a phenomenon, to be tested through research.
• Variable : Any factor or element that can be changed and measured in research.
• Literature Review : A comprehensive survey of existing research and publications on a specific topic.
• Methodology : The systematic plan and approach used to conduct research.
• Data Collection : The process of gathering information for analysis in research.
• Sample : A subset of a population selected for observation and analysis.
• Control Group : A group in an experiment that does not receive the treatment, used for comparison.
• Validity : The extent to which a research study measures what it intends to measure.
• Reliability : The consistency of a research study or measuring test.
• Abstract : A brief summary of a research study’s aims, methods, results, and conclusions.
• Population : The entire group of individuals or instances about whom the research is concerned.
• Ethics : Moral principles that govern a researcher’s conduct and the conduct of the research.
• Bias : A systematic error introduced into sampling or testing by selecting or encouraging one outcome over others.
• Pilot Study : A small-scale preliminary study conducted to evaluate feasibility, time, cost, risk, and adverse events.
• Peer Review : A process by which a research study is evaluated by experts in the same field before publication.
• Quantitative Research : Research that relies on numerical data and statistical methods.
• Qualitative Research : Research that relies on non-numerical data, such as interviews, observations, and textual analysis.
• Case Study : An in-depth study of a particular case, individual, group, or event.
• Longitudinal Study : Research that follows subjects over a long period to observe changes and developments.
• Cross-sectional Study : Research that analyzes data from a population at a specific point in time.
• Independent Variable : The variable that is manipulated to observe its effect on the dependent variable.
• Dependent Variable : The variable being tested and measured in an experiment.
• Confounding Variable : An outside influence that affects the dependent and independent variables, causing a spurious association.
• Operational Definition : A clear, precise, and measurable definition of a variable for the purposes of a study.
• Statistical Significance : The likelihood that a result or relationship is caused by something other than mere chance.
• Random Sample : A sample that fairly represents a population because each member has an equal chance of inclusion.
• Correlation : A measure of the relationship between two variables.
• Experimental Group : The group in an experiment that receives the treatment.
• Theoretical Framework : A structure that guides research by providing a clear perspective and basis for the study.
• Meta-analysis : A statistical technique that combines the results of multiple studies to determine overall trends.

Research Terms List

5 common research terminologies.

• Hypothesis : A testable prediction about the relationship between two or more variables.
• Variable : An element, feature, or factor that can be changed and measured in research.

Confusing Terms in Research

• Reliability : The consistency of a research study or measuring test over time.
• Independent Variable : The variable that is manipulated to observe its effect.
• Dependent Variable : The variable being tested and measured, which is affected by the independent variable.
• Random Assignment : Assigning participants to experimental and control groups by chance to minimize pre-existing differences.
• Descriptive Research : Research that aims to describe characteristics of a population or phenomenon.
• Explanatory Research : Research that seeks to explain the reasons behind a phenomenon or relationship.

Key Research Terms

1. abstract.

• A brief summary of the research paper, outlining the main points, purpose, methods, results, and conclusions.

2. Hypothesis

• A testable statement or prediction about the relationship between two or more variables.

3. Variable

• An element, feature, or factor that can be changed and measured in research. Includes independent, dependent, and control variables.

4. Literature Review

• A comprehensive survey of existing research and publications relevant to the research topic.

5. Methodology

• The systematic plan for conducting research, including the methods, techniques, and procedures used to collect and analyze data.

6. Qualitative Research

• Research that focuses on understanding phenomena through non-numerical data such as interviews, observations, and texts.

7. Quantitative Research

• Research that focuses on quantifying data and analyzing it statistically to draw conclusions.

8. Sampling

• The process of selecting a subset of individuals from a population to represent the whole group in research.

9. Data Collection

• The process of gathering information from various sources to answer research questions.

10. Data Analysis

• The process of examining, cleaning, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making.

Terms Synonymous to Research

Faq’s, what is a variable in research.

A variable is any characteristic, number, or quantity that can be measured or quantified in research.

What is the difference between qualitative and quantitative research?

Qualitative research explores concepts and experiences in-depth, while quantitative research involves measuring and analyzing numerical data.

What is a literature review?

A literature review summarizes existing research on a topic, identifying trends, gaps, and key findings.

What is a sample in research?

A sample is a subset of a population selected for study to represent the entire group.

What is a hypothesis?

A hypothesis is a testable prediction or educated guess about the relationship between two or more variables in a study.

What is data collection?

Data collection involves gathering information from various sources to address a research question or hypothesis.

What is an independent variable?

An independent variable is the variable that is manipulated or changed in an experiment to observe its effect.

What is a dependent variable?

A dependent variable is the variable being tested and measured in an experiment, affected by the independent variable.

What is a control group?

A control group is a group in an experiment that does not receive the treatment, used for comparison against the experimental group.

What is a research methodology?

Research methodology is the systematic plan for conducting research, including methods for data collection and analysis.

Text prompt

• Instructive
• Professional

10 Examples of Public speaking

20 Examples of Gas lighting

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Research Methods Key Term Glossary

Last updated 22 Mar 2021

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This key term glossary provides brief definitions for the core terms and concepts covered in Research Methods for A Level Psychology.

Don't forget to also make full use of our research methods study notes and revision quizzes to support your studies and exam revision.

The researcher’s area of interest – what they are looking at (e.g. to investigate helping behaviour).

A graph that shows the data in the form of categories (e.g. behaviours observed) that the researcher wishes to compare.

Behavioural categories

Key behaviours or, collections of behaviour, that the researcher conducting the observation will pay attention to and record

In-depth investigation of a single person, group or event, where data are gathered from a variety of sources and by using several different methods (e.g. observations & interviews).

Closed questions

Questions where there are fixed choices of responses e.g. yes/no. They generate quantitative data

Co-variables

The variables investigated in a correlation

Concurrent validity

Comparing a new test with another test of the same thing to see if they produce similar results. If they do then the new test has concurrent validity

Confidentiality

Unless agreed beforehand, participants have the right to expect that all data collected during a research study will remain confidential and anonymous.

Confounding variable

An extraneous variable that varies systematically with the IV so we cannot be sure of the true source of the change to the DV

Content analysis

Technique used to analyse qualitative data which involves coding the written data into categories – converting qualitative data into quantitative data.

Control group

A group that is treated normally and gives us a measure of how people behave when they are not exposed to the experimental treatment (e.g. allowed to sleep normally).

Controlled observation

An observation study where the researchers control some variables - often takes place in laboratory setting

Correlational analysis

A mathematical technique where the researcher looks to see whether scores for two covariables are related

Counterbalancing

A way of trying to control for order effects in a repeated measures design, e.g. half the participants do condition A followed by B and the other half do B followed by A

Covert observation

Also known as an undisclosed observation as the participants do not know their behaviour is being observed

Critical value

The value that a test statistic must reach in order for the hypothesis to be accepted.

After completing the research, the true aim is revealed to the participant. Aim of debriefing = to return the person to the state s/he was in before they took part.

Involves misleading participants about the purpose of s study.

Demand characteristics

Occur when participants try to make sense of the research situation they are in and try to guess the purpose of the research or try to present themselves in a good way.

Dependent variable

The variable that is measured to tell you the outcome.

Descriptive statistics

Analysis of data that helps describe, show or summarize data in a meaningful way

Directional hypothesis

A one-tailed hypothesis that states the direction of the difference or relationship (e.g. boys are more helpful than girls).

Dispersion measure

A dispersion measure shows how a set of data is spread out, examples are the range and the standard deviation

Double blind control

Participants are not told the true purpose of the research and the experimenter is also blind to at least some aspects of the research design.

Ecological validity

The extent to which the findings of a research study are able to be generalized to real-life settings

Ethical guidelines

These are provided by the BPS - they are the ‘rules’ by which all psychologists should operate, including those carrying out research.

Ethical issues

There are 3 main ethical issues that occur in psychological research – deception, lack of informed consent and lack of protection of participants.

Evaluation apprehension

Participants’ behaviour is distorted as they fear being judged by observers

Event sampling

A target behaviour is identified and the observer records it every time it occurs

Experimental group

The group that received the experimental treatment (e.g. sleep deprivation)

External validity

Whether it is possible to generalise the results beyond the experimental setting.

Extraneous variable

Variables that if not controlled may affect the DV and provide a false impression than an IV has produced changes when it hasn’t.

Face validity

Simple way of assessing whether a test measures what it claims to measure which is concerned with face value – e.g. does an IQ test look like it tests intelligence.

Field experiment

An experiment that takes place in a natural setting where the experimenter manipulates the IV and measures the DV

A graph that is used for continuous data (e.g. test scores). There should be no space between the bars, because the data is continuous.

This is a formal statement or prediction of what the researcher expects to find. It needs to be testable.

Independent groups design

An experimental design where each participants only takes part in one condition of the IV

Independent variable

The variable that the experimenter manipulates (changes).

Inferential statistics

Inferential statistics are ways of analyzing data using statistical tests that allow the researcher to make conclusions about whether a hypothesis was supported by the results.

Informed consent

Psychologists should ensure that all participants are helped to understand fully all aspects of the research before they agree (give consent) to take part

Inter-observer reliability

The extent to which two or more observers are observing and recording behaviour in the same way

Internal validity

In relation to experiments, whether the results were due to the manipulation of the IV rather than other factors such as extraneous variables or demand characteristics.

Interval level data

Data measured in fixed units with equal distance between points on the scale

Investigator effects

These result from the effects of a researcher’s behaviour and characteristics on an investigation.

Laboratory experiment

An experiment that takes place in a controlled environment where the experimenter manipulates the IV and measures the DV

Matched pairs design

An experimental design where pairs of participants are matched on important characteristics and one member allocated to each condition of the IV

Measure of central tendency calculated by adding all the scores in a set of data together and dividing by the total number of scores

Measures of central tendency

A measurement of data that indicates where the middle of the information lies e.g. mean, median or mode

Measure of central tendency calculated by arranging scores in a set of data from lowest to highest and finding the middle score

Meta-analysis

A technique where rather than conducting new research with participants, the researchers examine the results of several studies that have already been conducted

Measure of central tendency which is the most frequently occurring score in a set of data

Natural experiment

An experiment where the change in the IV already exists rather than being manipulated by the experimenter

Naturalistic observation

An observation study conducted in the environment where the behaviour would normally occur

Negative correlation

A relationship exists between two covariables where as one increases, the other decreases

Nominal level data

Frequency count data that consists of the number of participants falling into categories. (e.g. 7 people passed their driving test first time, 6 didn’t).

Non-directional hypothesis

A two-tailed hypothesis that does not predict the direction of the difference or relationship (e.g. girls and boys are different in terms of helpfulness).

Normal distribution

An arrangement of a data that is symmetrical and forms a bell shaped pattern where the mean, median and mode all fall in the centre at the highest peak

Observed value

The value that you have obtained from conducting your statistical test

Observer bias

Occurs when the observers know the aims of the study study or the hypotheses and allow this knowledge to influence their observations

Open questions

Questions where there is no fixed response and participants can give any answer they like. They generate qualitative data.

Operationalising variables

This means clearly describing the variables (IV and DV) in terms of how they will be manipulated (IV) or measured (DV).

Opportunity sample

A sampling technique where participants are chosen because they are easily available

Order effects

Order effects can occur in a repeated measures design and refers to how the positioning of tasks influences the outcome e.g. practice effect or boredom effect on second task

Ordinal level data

Data that is capable of being out into rank order (e.g. places in a beauty contest, or ratings for attractiveness).

Overt observation

Also known as a disclosed observation as the participants given their permission for their behaviour to be observed

Participant observation

Observation study where the researcher actually joins the group or takes part in the situation they are observing.

Peer review

Before going to publication, a research report is sent other psychologists who are knowledgeable in the research topic for them to review the study, and check for any problems

Pilot study

A small scale study conducted to ensure the method will work according to plan. If it doesn’t then amendments can be made.

Positive correlation

A relationship exists between two covariables where as one increases, so does the other

Presumptive consent

Asking a group of people from the same target population as the sample whether they would agree to take part in such a study, if yes then presume the sample would

Primary data

Information that the researcher has collected him/herself for a specific purpose e.g. data from an experiment or observation

Prior general consent

Before participants are recruited they are asked whether they are prepared to take part in research where they might be deceived about the true purpose

Probability

How likely something is to happen – can be expressed as a number (0.5) or a percentage (50% change of tossing coin and getting a head)

Protection of participants

Participants should be protected from physical or mental health, including stress - risk of harm must be no greater than that to which they are exposed in everyday life

Qualitative data

Descriptive information that is expressed in words

Quantitative data

Information that can be measured and written down with numbers.

Quasi experiment

An experiment often conducted in controlled conditions where the IV simply exists so there can be no random allocation to the conditions

Questionnaire

A set of written questions that participants fill in themselves

Random sampling

A sampling technique where everyone in the target population has an equal chance of being selected

Randomisation

Refers to the practice of using chance methods (e.g. flipping a coin' to allocate participants to the conditions of an investigation

The distance between the lowest and the highest value in a set of scores.

A measure of dispersion which involves subtracting the lowest score from the highest score in a set of data

Reliability

Whether something is consistent. In the case of a study, whether it is replicable.

Repeated measures design

An experimental design where each participants takes part in both/all conditions of the IV

Representative sample

A sample that that closely matched the target population as a whole in terms of key variables and characteristics

Retrospective consent

Once the true nature of the research has been revealed, participants should be given the right to withdraw their data if they are not happy.

Right to withdraw

Participants should be aware that they can leave the study at any time, even if they have been paid to take part.

A group of people that are drawn from the target population to take part in a research investigation

Scattergram

Used to plot correlations where each pair of values is plotted against each other to see if there is a relationship between them.

Secondary data

Information that someone else has collected e.g. the work of other psychologists or government statistics

Semi-structured interview

Interview that has some pre-determined questions, but the interviewer can develop others in response to answers given by the participant

A statistical test used to analyse the direction of differences of scores between the same or matched pairs of subjects under two experimental conditions

Significance

If the result of a statistical test is significant it is highly unlikely to have occurred by chance

Single-blind control

Participants are not told the true purpose of the research

Skewed distribution

An arrangement of data that is not symmetrical as data is clustered ro one end of the distribution

Social desirability bias

Participants’ behaviour is distorted as they modify this in order to be seen in a positive light.

Standard deviation

A measure of the average spread of scores around the mean. The greater the standard deviation the more spread out the scores are. .

Standardised instructions

The instructions given to each participant are kept identical – to help prevent experimenter bias.

Standardised procedures

In every step of the research all the participants are treated in exactly the same way and so all have the same experience.

Stratified sample

A sampling technique where groups of participants are selected in proportion to their frequency in the target population

Structured interview

Interview where the questions are fixed and the interviewer reads them out and records the responses

Structured observation

An observation study using predetermined coding scheme to record the participants' behaviour

Systematic sample

A sampling technique where every nth person in a list of the target population is selected

Target population

The group that the researchers draws the sample from and wants to be able to generalise the findings to

Temporal validity

Refers to how likely it is that the time period when a study was conducted has influenced the findings and whether they can be generalised to other periods in time

Test-retest reliability

Involves presenting the same participants with the same test or questionnaire on two separate occasions and seeing whether there is a positive correlation between the two

Thematic analysis

A method for analysing qualitative data which involves identifying, analysing and reporting patterns within the data

Time sampling

A way of sampling the behaviour that is being observed by recording what happens in a series of fixed time intervals.

Type 1 error

Is a false positive. It is where you accept the alternative/experimental hypothesis when it is false

Type 2 error

Is a false negative. It is where you accept the null hypothesis when it is false

Unstructured interview

Also know as a clinical interview, there are no fixed questions just general aims and it is more like a conversation

Unstructured observation

Observation where there is no checklist so every behaviour seen is written down in an much detail as possible

Whether something is true – measures what it sets out to measure.

Volunteer sample

A sampling technique where participants put themselves forward to take part in research, often by answering an advertisement

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Chapter 1: Introduction to Research Methods

1.4 Understanding Key Research Concepts and Terms

In this textbook you will be exposed to many terms and concepts associated with research methods, particularly as they relate to the research planning decisions you must make along the way. Figure 1.3 will help you contextualize many of these terms and understand the research process. This general chart begins with two key concepts: ontology and epistemology, advances through other concepts, and concludes with three research methodological approaches: qualitative, quantitative and mixed methods.

Research does not end with making decisions about the type of methods you will use; we could argue that the work is just beginning at this point. Figure 1.3 does not represent an all-encompassing list of concepts and terms related to research methods. Keep in mind that each strategy has its own data collection and analysis approaches associated with the various methodological approaches you choose. Figure 1.3 is intentioned to provide a general overview of the research concept. You may want to keep this figure handy as you read through the various chapters.

Ontology & Epistemology

Thinking about what you know and how you know what you know involves questions of ontology and epistemology. Perhaps you have heard these concepts before in a philosophy class? These concepts are relevant to the work of sociologists as well. As sociologists (those who undertake socially-focused research), we want to understand some aspect of our social world. Usually, we are not starting with zero knowledge. In fact, we usually start with some understanding of three concepts: 1) what is; 2) what can be known about what is; and, 3) what the best mechanism happens to be for learning about what is (Saylor Academy, 2012). In the following sections, we will define these concepts and provide an example of the terms, ontology and epistemology.

Ontology is a Greek word that means the study, theory, or science of being. Ontology is concerned with the what is or the nature of reality (Saunders, Lewis, & Thornhill, 2009). It can involve some very large and difficult to answer questions, such as:

• What is the purpose of life?
• What, if anything, exists beyond our universe?
• What categories does it belong to?
• Is there such a thing as objective reality?
• What does the verb “to be” mean?

Ontology is comprised of two aspects: objectivism and subjectivism. Objectivism means that social entities exist externally to the social actors who are concerned with their existence. Subjectivism means that social phenomena are created from the perceptions and actions of the social actors who are concerned with their existence (Saunders, et al., 2009). The table below provides an example of a similar research project to be undertaken by two different students. While the projects being proposed by the students are similar, they each have different research questions. Read the scenario and then answer the questions that follow.

Subjectivist and objectivist approaches (adapted from Saunders et al., 2009)

Ana is an Emergency & Security Management Studies (ESMS) student at a local college. She is just beginning her capstone research project and she plans to do research at the City of Vancouver. Her research question is: What is the role of City of Vancouver managers in the Emergency Management Department (EMD) in enabling positive community relationships? She will be collecting data related to the roles and duties of managers in enabling positive community relationships.

Robert is also an ESMS student at the same college. He, too, will be undertaking his research at the City of Vancouver. His research question is: What is the effect of the City of Vancouver’s corporate culture in enabling EMD managers to develop a positive relationship with the local community? He will be collecting data related to perceptions of corporate culture and its effect on enabling positive community-emergency management department relationships.

Before the students begin collecting data, they learn that six months ago, the long-time emergency department manager and assistance manager both retired. They have been replaced by two senior staff managers who have Bachelor’s degrees in Emergency Services Management. These new managers are considered more up-to-date and knowledgeable on emergency services management, given their specialized academic training and practical on-the-job work experience in this department. The new managers have essentially the same job duties and operate under the same procedures as the managers they replaced. When Ana and Robert approach the managers to ask them to participate in their separate studies, the new managers state that they are just new on the job and probably cannot answer the research questions; they decline to participate. Ana and Robert are worried that they will need to start all over again with a new research project. They return to their supervisors to get their opinions on what they should do.

Before reading about their supervisors’ responses, answer the following questions:

• Is Ana’s research question indicative of an objectivist or a subjectivist approach?
• Is Robert’s research question indicative of an objectivist or a subjectivist approach?
• Given your answer in question 1, which managers could Ana interview (new, old, or both) for her research study? Why?
• Given your answer in question 2, which managers could Robert interview (new, old, or both) for his research study? Why?

Ana’s supervisor tells her that her research question is set up for an objectivist approach. Her supervisor tells her that in her study the social entity (the City) exists in reality external to the social actors (the managers), i.e., there is a formal management structure at the City that has largely remained unchanged since the old managers left and the new ones started. The procedures remain the same regardless of whoever occupies those positions. As such, Ana, using an objectivist approach, could state that the new managers have job descriptions which describe their duties and that they are a part of a formal structure with a hierarchy of people reporting to them and to whom they report. She could further state that this hierarchy, which is unique to this organization, also resembles hierarchies found in other similar organizations. As such, she can argue that the new managers will be able to speak about the role they play in enabling positive community relationships. Their answers would likely be no different than those of the old managers, because the management structure and the procedures remain the same. Therefore, she could go back to the new managers and ask them to participate in her research study.

Robert’s supervisor tells him that his research is set up for a subjectivist approach. In his study, the social phenomena (the effect of corporate culture on the relationship with the community) is created from the perceptions and consequent actions of the social actors (the managers); i.e., the corporate culture at the City continually influences the process of social interaction, and these interactions influence perceptions of the relationship with the community. The relationship is in a constant state of revision. As such, Robert, using a subjectivist approach, could state that the new managers may have had few interactions with the community members to date and therefore may not be fully cognizant of how the corporate culture affects the department’s relationship with the community. While it would be important to get the new managers’ perceptions, he would also need to speak with the previous managers to get their perceptions from the time they were employed in their positions. This is because the community-department relationship is in a state of constant revision, which is influenced by the various managers’ perceptions of the corporate culture and its effect on their ability to form positive community relationships. Therefore, he could go back to the current managers and ask them to participate in his study, and also ask that the department please contact the previous managers to see if they would be willing to participate in his study.

As you can see the research question of each study guides the decision as to whether the researcher should take a subjective or an objective ontological approach. This decision, in turn, guides their approach to the research study, including whom they should interview.

Epistemology

Epistemology has to do with knowledge. Rather than dealing with questions about what is, epistemology deals with questions of how we know what is.  In sociology, there are many ways to uncover knowledge. We might interview people to understand public opinion about a topic, or perhaps observe them in their natural environment. We could avoid face-to-face interaction altogether by mailing people surveys to complete on their own or by reading people’s opinions in newspaper editorials. Each method of data collection comes with its own set of epistemological assumptions about how to find things out (Saylor Academy, 2012). There are two main subsections of epistemology: positivist and interpretivist philosophies. We will examine these philosophies or paradigms in the following sections.

Research Methods for the Social Sciences: An Introduction Copyright © 2020 by Valerie Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Research Process

• Getting Started with Research: Credo
• Brainstorming

Identify Key Search Terms

• Finding Books
• Finding Articles
• Library Search Strategies
• Using Google
• CRAAP Method
• The ACT UP Method
• Evaluating News Sources
• More Resources
• Chicago (Turabian)
• Presentation and Printing Resources This link opens in a new window

Introduction to identifying key search terms

Before you begin searching for scholarly sources, you should identify key search terms that can help you.

Identifying subjects

How to Identify Search Terms

Use your research topic, research question, and the important information you found during your background research to help you identify key search terms. Here are some examples that can help you with this stage of the research process.

• Example: How will global warming affect Louisiana coastal communities?
• Example: How will global warming affect Louisiana coastal communities? ​
• Choose keywords that you can use to search the databases. Sometimes using exact words or terms won’t generate useful information, so try using synonyms instead. For example:

Tip: If you are struggling to find synonyms, try creating a mind map like you would if your were brainstorming.  Thesaurus.com is also a great source for generating synonyms.

• With your list of keywords and synonyms, you can now begin looking for sources using Ellender Library's online catalog and databases.

Credit for Page

This page was created by Magen Nosworthy (Fall 2018 ENGL 489)

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