Bias: a lack of balance and accuracy in the use of research methods. It can appear at any phase of research, from deciding on a sampling frame, sampling, to data collection and analysis. Bias also arises in the identity of the researcher through assumptions and ideas related to his or her own culture that may influence data collection and analysis. Bias interfere with the extent to which results are valid and accurate, whether or not the research is reliable, and the potential for results to be representative of, or generalizable to, a wider population. Click here to access a brief article from the National Institutes of Health on research bias.
Case Study: the collection and presentation of in-depth information about a specific individual, group, or community. Often these data represent the subjective experiences of an individual or group. Click here to access more information on the case study approach to research.
Causality: the relation between cause and effect. Causality is the agency that links one process or event (the cause) with another process, state, or event (the effect). The first of these is normally understood to be at least partly responsible for the occurrence of the second, thus the second is dependent upon the first. Causality is an abstraction based upon experience that is used to show and explain how change happens in the world. Below is a very useful video explaining causality and how it relates to research.
Cultural Relativism: the idea that cultures are value-neutral. This means that rather than various cultures being a better or worse ways of organizing behavior, they are simply different. In anthropology, this idea has been used to make sense out of behaviors and values that seem alien or morally wrong to an outside observer; it has also been used to raise awareness of the potential for bias by an observer. The concept has been debated in anthropology and has raised concern that it inherently leads to moral relativism. Most modern anthropologists use the idea of cultural relativism as a way to bracket off one’s own cultural assumptions and biases to the extent possible. Here is a brief article on cultural relativism by anthropologist Clifford Geertz.
Data: factual information, collected through systematic methods, that is used as a basis for reasoning and analysis of a phenomenon.
Deductive Reasoning: a type of reasoning in which conclusions are formulated about particulars from general or universal premises. Here’s Monty Python’s take on deductive reasoning.
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. Check out the video under the entry for independent variables for more information on the difference between dependent and independent variables.
Emic: an approach to the study or description of a language or culture that focuses on its internal elements and logic and their functioning rather than in terms of any existing external scheme. The term can also refer to the native explanation for a behavior or cultural pattern. The video below will help you to understand the differences between emic and etic perspectives as they are understood by cultural anthropologists.
Etic: an approach to the study or description of a language or culture that is general, nonstructural, and objective in its perspective. It is typically explanations for behavior from the perspective of the scientist/researcher observing a culture or language.
Epistemology: theory of knowledge that questions how we know things, how knowledge is constructed, and what constitutes valid knowledge. Here is a very detailed definition/discussion of epistemology from the Stanford online dictionary of philosophy.
Ethnography: method for studying study groups and/or cultures over an extended period of time using a variety of qualitative (and sometimes quantitative) research techniques. Ethnography employs participant observation, which is intended to allow researchers to understand a group through immersion into its lifestyles. This allows for a detailed, in-depth, understanding of human experience. Check out the TEDx video below for a nice discussion of the use of ethnography in business.
Field Studies: research studies carried out in natural settings, rather than in laboratories, classrooms, or other structured environments.
Focus Groups: small, roundtable discussion groups charged with examining or discussing topics or problems associated with a research project. In some cases, these may also involve discussion of solutions to identified problems. Focus groups usually consist of 4-12 participants and are guided by moderators to keep the discussion moving and collect data. Here is more on focus group research from the Robert Wood Johnson Foundation.
Grounded Theory: an approach to research in which theories emerge from observing a group rather than being brought to the context of observation. Theories are grounded in the group’s observable experiences and interpretations, but researchers add their own insight into why those experiences exist. Click here to access the website Grounded Theory Online.
Hypothesis: a tentative explanation or educated guess based on theory or observation that is used to predict a causal relationship between variables. Click here to review some examples of hypotheses.
Independent Variable: the conditions or variables of an experiment that are systematically manipulated by the researcher or a variable that is not impacted by the dependent variable, but that itself impacts the dependent variable. Check out the video below for more information on the difference between dependent and independent variables.
Inductive Reasoning: a type of reasoning in which a generalized conclusion is formulated generated based on particular instances. Below is a video on the difference between inductive and deductive approaches to reasoning.
Naturalistic Observation: observation of behaviors and events in natural settings rather than in experimental contexts that involve manipulation of variables or other types of interference.
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. Click here for a detailed discussion of logic and ontology from the Stanford online dictionary of philosophy.
Organization: For the purposes of MMEO, and organization is an institutionalized structure that is formed for a specific purpose. Examples of organizations are businesses, academic institutions, religious institutions, or government institutions.
Participant observation: a form of qualitative research that involves participating in the activities of the people being observed as a way of developing an experience-near understanding of their behaviors and ideas.
Phenomenology: a qualitative research approach that focuses on meaning expressed by individuals through their lived experience of a particular idea, concept, or event. This link will take you to more information on phenomenology.
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.
Probability: the likelihood that a phenomenon will occur randomly. As a statistical measure, it is represented as p.
Qualitative research: a systematic approach to creating knowledge about how people interpret their surroundings, construct meaning, and interpret the meanings they construct. Qualitative research relies upon subtle and complex techniques of observation, recording data, and writing to develop an interpretive framework for analyzing and explaining why people do what they do and think what they think.
Quantitative research: Quantitative research focuses on identifying objective measurements of phenomena such as human behavior. In human subjects research it makes use of statistical, mathematical, and numerical analysis of empirical data collected using instruments such as questionnaires or through analyzing and manipulating pre-existing statistical data using computational techniques. Quantitative research uses numerical data to draw general conclusions across groups of people as a way of explaining particular behaviors or phenomena. This link to a site as USC will give you more details on quantitative research.
Questionnaire: structured groups of questions used to gather information, attitudes, or opinions. Questionnaires can be either quantitative, including forced-choice questions, or qualitative, including open-ended questions.
Random Sampling: a process used in research to draw a sample of a population that does not reflect any pattern or order beyond chance.
Reliability: the extent to which a research method yields consistent results. If the observational or measurement instrument is reliable, then administering it to similar groups should yield similar results. Reliability is a prerequisite for validity. If a data collection approach is unreliable, then cannot produce trustworthy results.
Rigor: degree to which research methods are carefully designed and carried out.
Sample: any population researched in a study. In many studies, researchers often try to select a “sample population” that is believed to be representative of the behaviors or other qualities (race, ethnicity, gender) of people for whom results will be generalized. This video will help you understand different types of sampling and the goals in sampling.
Sampling Error: the degree to which the results from the sample deviate from those that would be obtained from the entire population. This can be a result of random error in the selection of participants and any corresponding reduction in reliability that arises as a result of that error.
Standard Deviation: a measure used to quantify how much variation or dispersion there is in a set of data values. A low standard deviation means that the data points tend to be close to the mean; a high standard deviation means the data points are spread out over a wider range of values and further from the mean.
Statistical Analysis: application of statistical methods and theory to the collection, presentation, and interpretation of numerical data.
Statistical Significance: in any experiment or observation that involves using a sample from a population, statistical significance refers to the likelihood that a behavior or set of behaviors is due to chance. The probability that the null hypothesis can be rejected at a predetermined significance level [0.05 or 0.01].
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.
Triangulation: a multi-method or pluralistic approach to research that uses a variety of methods to collect data from different viewpoints. This produces a complex and multi-faceted data set that helps in checking the validity of findings.
Unit of Analysis: the thing being observed, analyzed, and for which data are collected in the form of variables.
Validity — the degree to which a study accurately represents and assesses the specific phenomenon a researcher wants to measure. This brief video will help you to understand the difference between validity and reliability in research.
Variable: any characteristic or trait that can vary from person to person. Race, gender, education level, hair color, age, political beliefs, religion are all examples of variables. This link will take you to a website that provides more detail on variables.