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.
The probability that the results of a statistical test were due to chance. A p-value greater than .05 is usually interpreted to mean that the results were not statistically significant. Sometimes researchers use a p-value of .01 or a p-value of .10 to indicate whether a result is statistically significant. The lower the p-value the more rigorous the criteria for concluding significance.
Paired Comparison Method
The paired comparison method is a research design that yields scores based on respondents' ratings of pairs of items. For example, a respondent is presented with a set of binary items and asked to indicate which of the choices he/she prefers or is more applicable.
This test, which is sometimes called the dependent sample t-test, is usually used to determine whether the mean difference between two sets of observations for the same subjects is zero. In a paired sample t-test, each participant or subject is measured twice. It is often used to determine whether an intervention brought about a change in some characteristic of respondents (e.g., respondents' math knowledge). To perform a paired t-test, respondents' math knowledge would be measured prior to the intervention, then the intervention would be performed (e.g., teaching a class on math), then respondent's math knowledge would be measured after the intervention. The change from before to after the intervention is used to assess whether the intervention was successful.
A type of longitudinal study in which data are collected from the same group of individuals (a panel) at two or more points in time. Although the sample selected for a panel study often include individuals (e.g., children, young adults), they may sample from other populations such as households, schools, and classrooms and collect data on these over a period of time.
In statistics, a parameter is a characteristic of a population. It is a numerical quantity that tells us something about a population and is distinct from a statistic, which is a characteristic of a sample.
A field research method whereby the researcher develops knowledge of the composition of a particular setting or society by taking part in the everyday routines and rituals alongside its members. A principle goal of participant observation is develop an understanding of a setting from a member's perspective, which may be accomplished through both informal observations and conversations as well as in-depth interviews.
The investigator takes part in the group activity that the researcher plans to study. The researcher also reveals to the group that s/he is studying the group's activities.
Participatory Action Research
Participatory action research (PAR) is a type of action research that involves stakeholders as equal partners. For example, researchers may work together with representatives from American Indian tribes to design a study that can be used to improve how health and education services are delivered to their people.
A special use of multiple regression where the goal is to discern and assess the effects of a set of variables on an outcome. Path analysis is a form of analysis that looks explicitly at cause. The pattern of relationships among variables is described by a path diagram with arrows used to indicate the directions of the causal relationships between them. Multiple regression is used to estimate the strength and direction of the relationships.
Pearson's Correlational Coefficient
Usually denoted by r, this is a measure of the degree to which two variables are associated. Pearson's correlation coefficient is used when the two variables are continuous. The coefficient can have values ranging from -1 to +1. If the coefficient is between 0 and +1, the variables are positively correlated, which means they both tend to increase (or decrease) in tandem. For example, children's height and weight are positively correlated because as height increases weight also tends to increase. If the coefficient is between 0 and -1, the variables are negatively correlated, which means as one increases the other decreases. For example, the number of days children are absent from school is negatively correlated with children's reading and math test scores because as the number of days children are absent increases their scores on reading and math tests decrease (when lower test scores indicate poorer performance in reading and math). The closer the coefficient is to either -1 or +1, the stronger the association between the two variables. This is also called a Product Moment Correlation.