The research glossary defines terms used in conducting social science and policy research, for example those describing methods, measurements, statistical procedures, and other aspects of research; the child care glossary defines terms used to describe aspects of child care and early education practice and policy.
Selective Observation
The act of only attending to observations that correspond to current belief.
Self-Selection Sampling
Self-selection sampling is a type of non-probability sampling where the decision to take part in the study is left up to the potential participants themselves. For example, individuals may be invited to participate in a public opinion survey as part of a local news broadcast, or an invitation to participate in a survey may be sent to all members of an organization asking them to express their opinions about a particular issue.
Semantic Differential Scale
A type of rating scale that is designed to measure the meaning of things or objects. In research a semantic differential scale or a series of such scales are often used to measure attitudes. Participants are presented an object, event or concept that is followed by a series of opposing adjectives separated by a sequence of unlabeled categories. Participants are asked to indicate their position relative to the two adjectives. For example, teachers may be asked how they would rate the professional development opportunities at their program using bipolar adjectives such as good-bad, interesting-boring, relevant-irrelevant.
Semi-Structured Interview
A method of data collection in which the interviewer uses a pre-determined list of topics or questions to gather information from a respondent. The interviewer, however, may stray from the list to follow-up on things the respondent says during the interview.
Sensitivity Analysis
Sensitivity analysis is a tool that is used to assess the robustness of the findings or conclusions based on primary analyses of data. It is used to assess the impact, effect or influence of key assumptions or variations—such as different methods of analysis, definitions of outcomes, protocol deviations, missing data, and outliers—on the overall conclusions of a study.
Sequential Hypothesis Testing
In statistics, sequential hypothesis testing or sequential analysis is a type of statistical analysis where the sample size is not set in advance. Instead, data are evaluated as they are collected, and sampling is stopped in accordance with a pre-defined stopping rule as soon as significant results are observed. An advantage of this approach is that fewer sampled cases may be required to meet the objectives of the research, thus reducing costs.
Significance Level
The probability of rejecting the null hypothesis in a statistical test when it is true (Type I Error). The significance level is set before the statistical analysis is undertaken. A commonly used significance level is .05, which indicates a 5% risk of concluding that a difference exists (group means are different or a correlation is different from zero) when there is no actual difference. If a statistical test (e.g., t-test or F-test) indicate that the changes of finding the observed results by chance are unlikely (p .05) the findings are classified as statistically significant.
Simple Linear Regression
A statistical technique that measure the relationship between a dependent (outcome) variable and one independent (predictor) variable.
Simple Random Sampling
The basic sampling technique where a group of subjects (a sample) for study is selected from a larger group (a population). Each individual is chosen entirely by chance and each member of the population has an equal chance of being included in the sample.
Simulation
Simulation is a tool used by researchers to study complex problems and processes. Data are created according to a known model or theory and data analysis is used to explore how well the data fit the model under different sets of assumptions and conditions. Unlike in the real world, the researcher controls all of the factors affecting the data and can manipulate these systematically to see how each alone and in combination affect their findings.