Refer to this page for definitions and explanations of common terms used in research. This list is not exhaustive and is intended as a quick reference. Main menu | Comments/Suggestions
| Understanding research terminology | Demystifying nursing research terminology. Part 1 |
| Research | The process of systematic study or investigation to discover new knowledge or expand on existing knowledge |
| Research method | A means of collecting data |
| Theory | A theory is a set of interrelated concepts, definitions, and propositions that explains or predicts events or situations by specifying relations among variables. Theories can be used as the conceptual basis for understanding, analyzing, and designing ways to investigate relationships within social systems. |
| Population vs. Sample | A population includes all members of interest whereas the sample includes only a portion (subset) of the population. |
| Sampling | The process of selecting a subset of participants from the pool of all potential participants |
| Probability sampling | The process of selecting a subset of participants for which all individuals in a sampling frame have a known probability of being selected to participate. Simple random sampling is a common example where members of the sample are selected randomly, and each has the same probability of being selected. |
| Nonprobability sampling | The process of selecting a subset of participants for which all individuals in a sampling frame do not have a known probability of being selected to participate. This is often used when researchers have reason to be selective in who participates, like studying only those who have experienced a particular phenomenon. |
| Variables | An attribute or characteristic that can be measured and takes on different values (changes) among and between participants. |
| Independent variable | An attribute or characteristic that the researcher manipulates or changes, and which the researcher expects has an effect on the dependent variable(s) |
| Dependent variable | An attribute or characteristic that changes as a result of another variable (typically the independent variable) |
| Moderating variables (Moderators) | An attribute or characteristic that changes the strength of an effect between variables (typically the independent and dependent variables) |
| Mediating variables
(Mediators) |
An attribute or characteristic that explains how the relationship between variables happens |
| Confounding (extraneous) variables | An attribute or characteristic that is not known or measured, and may have an effect on another variable (typically the dependent variable) |
| Discrete variables | A variable whose values can be divided into distinct groups and can be counted like breeds of dogs or grade in school. |
| Continuous variables | A variable with infinite number of values like height and weight. |
| Nominal variable | Discrete variables for which the order does not matter like breeds of dogs. |
| Ordinal variable | Discrete variables for which the order has a meaning like grade in school. |
| Ratio variable | Continuous variable that includes a value of zero that is meaningful like temperature. |
| Hypothesis | An informed and educated prediction or explanation about a relationship or phenomena. |
| Outcomes | The expected result of interest; often the dependent variable. |
| Parameter | A characteristic or attribute of a population. |
| Qualitative methods | Commonly refers to a research approach that emphasizes non-numerical data |
| Quantitative methods | Commonly refers to a research approach that emphasizes numerical data |
| Mixed methods | Commonly refers to a research approach that integrates both numerical and non-numerical data |
| Rigor | Refers to the degree of methodological soundness; how well the researcher(s) adhered to the process of conducting research based on the type of method used |
| Validity | The degree to which we are observing or measuring what we think we are (precision) |
| Reliability | The degree to which we will obtain the same results with repeated observations or measures (accuracy) |
| Bias | Something that happens during the course of a study that is not part of the research protocol and which alters the results. |
| Generalizability | The degree to which research results or patterns found in a sample population will also be found in the wider population which the sample represents. |
| Variance | The difference or the variation that occurs in measures of variables within a sample. |
| Research or study protocol | The research plan developed by the researcher that should be followed when carrying out the study. |
| Primary data | Data collected from original sources, not from something already published |
| Secondary data | Data collected from sources that have been published, not collected from original sources |
| p-value | A p-value helps you determine the significance of your results. The p-value is a number between 0 and 1 and interpreted in the following way:
· A small p-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis, so you reject the null hypothesis in favor of the alternative hypothesis · A large p-value (> 0.05) indicates weak evidence against the null hypothesis, so you fail to reject the null hypothesis |
| Null hypothesis | The hypothesis that there is no significant difference between groups |
| Alternative hypothesis | The hypothesis that there is a significant difference between groups; typically indicates that an intervention had an effect |
| Confidence interval | This is a measure of precision or how confident we can be that the values of the thing(s) we measured in our study sample represent the true or actual values of that thing(s) in the larger population. It takes into consideration both the range of values measured (lowest and highest) and how the range compares to the average value of the measure (variability). |
| Sensitivity | The degree to which an instrument can detect changes to a measure; in epidemiology referred to as a true positive rate |
| Specificity | The degree to which an instrument detects only changes in a given measure; in epidemiology referred to as a true negative rate |
| Descriptive Statistics | Numerical summaries of data, typically the characteristics or attributes of study participants. |
| Frequencies | The number of times something occurs, a count of an occurrence |
| Measures of central tendency | A single value that describes the way in which a group of data cluster around a central value. |
| Mean | Average of a set of numbers calculated by adding the values and dividing the sum by the number of values. |
| Median | When a set of values is ordered from low to high, the median is the value that is in the middle of the list. |
| Mode | For a set of values, it is the value that is recorded most often. |
| Inferential statistics | Statistical tests used to draw conclusions from a sample to the larger population |
| Correlation | A measure of the direction and degree of a relationship between two variables. |
| Inductive | Using specific observations to develop generalizations, like a theory |
| Deductive | Applying generalities, like a theory, to a specific occurrence. |
| Clinical significance | The practical importance of a finding or result within the context of health care. |
| Statistical significance | The probability that a result could be due to chance (versus from introduction on an intervention) |
| Coding | The process of naming a group of observations or responses that are similar.
The process of converting responses for ease of data analysis. For example, educational attainment: Less than high school=0; High school=1; More than high school=2 |