Term
|
Definition
| a process of ongoing feedback on performance. The purposes are to identify aspects of performance that need to improve and to offer corrective suggestions. |
|
|
Term
|
Definition
| a process of identifying larger patterns and trends in performance and judging these summary statements against criteria to obtain performance ratings. |
|
|
Term
|
Definition
| an experimental procedure in which neither the subjects of the experiment nor the persons administering the experiment know the critical aspects of the experiment; "a double-blind procedure is used to guard against both experimenter bias and placebo effects" |
|
|
Term
|
Definition
Univariate analysis explores each variable in a data set, separately. It looks at the range of values, as well as the central tendency of the values. It describes the pattern of response to the variable. It describes each variable on its own.
Descriptive statistics describe and summarize data. Univariate descriptive statistics describe individual variables. |
|
|
Term
|
Definition
| a statistical technique for amalgamating, summarising, and reviewing previous quantitative research. By using meta-analysis, a wide variety of questions can be investigated, as long as a reasonable body of primary research studies exist. Selected parts of the reported results of primary studies are entered into a database, and this "meta-data" is "meta-analyzed", in similar ways to working with other data - descriptively and then inferentially to test certain hypotheses. The appeal of meta analysis is that it in effect combines all the research on one topic into one large study with many participants. The danger is that in amalgamating a large set of different studies the construct definitions can become imprecise and the results difficult to interpret meaningfully. |
|
|
Term
|
Definition
| express quantitatively the degree of variation or dispersion of values in a population or in a sample . Along with measures of central tendency , measures of dispersion are widely used in practice as descriptive statistics . Some measures of dispersion are the standard deviation , the average deviation , the range , the interquartile range . |
|
|
Term
|
Definition
| roblem that affects most longitudinal studies. For example, in a panel study, some of the original participants will not be participating at the end of the study — as a consequence of death, emigration, or failure to provide a forwarding address when moving house. |
|
|
Term
|
Definition
or panel study is a form of longitudinal study used in medicine, social science and ecology. It is one type of study design and should be compared with a cross-sectional study.
A cohort is a group of people who share a common characteristic or experience within a defined period (e.g., are born, leave school, lose their job, are exposed to a drug or a vaccine, etc.). Thus a group of people who were born on a day or in a particular period, say 1948, form a birth cohort. The comparison group may be the general population from which the cohort is drawn, or it may be another cohort of persons thought to have had little or no exposure to the substance under investigation, but otherwise similar. Alternatively, subgroups within the cohort may be compared with each other. |
|
|
Term
|
Definition
measure the same sample of respondents at different points in time. Unlike trend studies, panel studies can reveal both net change and gross change in the dependent variable. Additionally, panel studies can reveal shifting attitudes and patterns of behavior that might go unnoticed with other research approaches. Depending on the purpose of the study, researchers can use either a continuous panel, consisting of members who report specific attitudes or behavior patterns on a regular basis, or an interval panel, whose members agree to complete a certain number of measurement instruments only when the information is needed. In general, panel studies provide data suitable for sophisticated statistical analysis and might enable researcher to predict cause-effect relationships.
Panel data are particularly useful in predicting long-term or cumulative effects which are normally hard to analyze in a one-shot case study (or cross-sectional study). |
|
|
Term
|
Definition
| the researcher follows the participants and measures or obseves the behavior of the participants. Depending on the use of randomization, the prospective design is categorized into clinical trials or cohort design. The researcher waits for the future events in both designs. |
|
|
Term
|
Definition
| the researcher gathers the data at once and classifies the participants simultaneously into the group categories. If there are only two categories such as yes (case) and no (control) group, it is called case-control studies. If there are more than two categories, it is called cross-sectional studies. |
|
|
Term
|
Definition
the researcher gathers the data at once like case-control studies and then classifies them simultaneously on the classification (more than two categories) and their current responses.
For instance, the researcher wants to know the relationship between mathematics performance and the number of hours spent watching television a day. She gathers information on the average number of hours spent watching TV and the performance of the qualifying mathematics examination. Because she gathers data at once and classifies the students based on the number of hours (more than 2 classifications in the cross-sectional study) and the math performance, it is the cross-sectional design. |
|
|
Term
|
Definition
| a complex form of cluster sampling. Using all the sample elements in all the selected clusters may be prohibitively expensive or not necessary. Under these circumstances, multistage cluster sampling becomes useful. Instead of using all the elements contained in the selected clusters, the researcher randomly selects elements from each cluster. Constructing the clusters is the first stage. Deciding what elements within the cluster to use is the second stage. The technique is used frequently when a complete list of all members of the population does not exist and is inappropriate. |
|
|
Term
|
Definition
When we consider a person good (or bad) in one category, we are likely to make a similar evaluation in other categories.
It is as if we cannot easily separate categories. It may also be connected with dissonance avoidance, as making them good at one thing and bad at another would make an overall evaluation (which we do anyway) difficult. |
|
|
Term
|
Definition
| happens when our attention is drawn to answers or observations that confirm our pre-existing beliefs. It's a lot like selective hearing (i.e., when people, especially children, hear only the things they want to hear). For example, if I hypothesize that blacks are more likely than whites to speed, I am probably likely to note the blacks who are speeding while paying less attention to speeding whites and blacks who are not speeding. A better approach to this study would be to write down the speed of every car going by and the race of the driver. I could then make tables and compare the percentages of speeding drivers of each race. Chances are that I'll find that race isn't related to one's likelihood of speeding. |
|
|
Term
|
Definition
| generalizing to others who are different from one's research population. This happens all the time. A study in New York City finds a high proportion of gang members and school administrators in rural America panic and institute draconian measures intended to stem the proliferation of gangs in their districts. A parenting program works in one community, so planners automatically assume it will work in theirs. A new study program raises grades for high school students, so colleges clamor to include it in their curriculum. All three of these examples illustrate how quickly some people take research findings as absolute. Who knows, maybe the findings actually do generalize. The problem is that you can't make that assumption. |
|
|
Term
|
Definition
| the study of interpretation theory, and can be either the art of interpretation, or the theory and practice of interpretation. Traditional hermeneutics — which includes Biblical hermeneutics — refers to the study of the interpretation of written texts, especially texts in the areas of literature, religion and law. Contemporary, or modern, hermeneutics encompasses not only issues involving the written text, but everything in the interpretative process. This includes verbal and nonverbal forms of communication as well as prior aspects that affect communication, such as presuppositions, preunderstandings, the meaning and philosophy of language, and semiotics.[1] |
|
|
Term
|
Definition
a situation that can occur when a researcher or analyst makes an inference about an individual based on aggregate data for a group. For example, a researcher might examine the aggregate data on income for a neighbourhood of a city, and discoverer that the average household income for the residents of that area is $30,000.
To state that the average income for residents of that area is $30,000 is true and accurate. No problem there. The ecological fallacy can occur when the researcher then states, based on this data, that people living in the area earn about $30,000. This may not be true at all, and may be an ecological fallacy. This fallacy assumes that individual members of a group have the average characteristics of the group at large. Stereotypes are one form of ecological fallacy, which assumes that groups are homogeneous. |
|
|
Term
|
Definition
A major problem for empirical researchers is the nature of the connection between the language of theory and the language of observation. Rules of correspondence is a term sometimes applied to the means, criteria, and assumptions underlying attempts to connect these two levels, by means of common expressions (see B. Hindess The Use of Official Statistics in Sociology, 1973
). In sociology, the passage from observation to conceptualization and back again requires a close examination of the manner in which our observations are organized and categorized (for example according to statistical criteria, tacit knowledge, or background expectancies), as well as to the operationalization of the concepts deployed to organize data. |
|
|
Term
|
Definition
| If the researcher is attempting to measure a construct with multiple indicator variables, then the researcher must demonstrate that the items measure the same thing. There are several methods of doing this, with varying meanings of and stringency for testing for unidimensionality. Some of these methods are: Cronbach's alpha or Factor Analysis |
|
|
Term
|
Definition
a term coined by Barney Glaser and Anselm Strauss in 1967 in the context of social research to describe the process of choosing new research sites or research cases to compare with one that has already been studied. It is one of the tools of qualitative research.
The goal of theoretical sampling is not the same as with the probabilistic sampling; the researcher's goal is not the representative capture of all possible variations, but to gain a deeper understanding of analysed cases and facilitate the development of analytic frame and concepts used in their research.
Theoretical sampling can be viewed as a technique of data triangulation: using independent pieces of information to get a better fix on something that is only partially known or understood. |
|
|
