Glossary
Glossary | |
These is glossary of research key terms. This glossary is intended as an aid to
professionals and non-professionals who find the world of research
somewhat intimidating. While it is impossible to cover all the terms
that can be confusing, this document briefly defines some of the more
common terms and concepts. | |
| You can always search for entries (regexp permitted). | |
|
Submit Term | |
| All | |
| Pages: «1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 » | |
| Term | Definition |
| Interactionism | Meaning is created by interactions between people. eg. the Looking-glass self. |
| Internal validity | Refers to the extent to which changes in the dependent variable (the observed effects) can be attributed to the independent variable rather than to extraneous variables. |
| Interpretation | 1. A term used in the analysis of the relationship between three variables, the elaboration model, to refer to the situation where a control variable is found to be the mediating factor in a bivariate relationship. 2. outcome of elaboration in which the control variable shows how one variable is related to another. |
| Interrater reliability (interobserver re | A measure of the consistency between the ratings/values assigned to an attribute that is being rated or observed; it is usually expressed as a percentage of agreement between two raters/observers or as a coefficient of agreement which may then be expressed as a probability. Usually employed by researchers using structured observation techniques. |
| Intersubjectivity | By sharing time and space, two actors communicate in a process of understanding. |
| Intertextuality | Meaning is constantly being produced by the relationship between texts. |
| Interval level of measurement | 1. A level of measurement in which the ratios of measured values are not meaningful, which is to say that they do not correspond to similar relationships among the objects measured. The classic example of interval measurement is the measurement of temperature using Fahrenheit and Centigrade scales. If it is 80ºF in Tulsa and 40ºF in Juneau, you cannot say it is twice as hot in Tulsa. Here is one clue that this is not meaningful. Suppose we measured the temperature in Centigrade instead of Fahrenheit. The formula for converting Fahrenheit to Centigrade is C=(F-32)*5/9. So in Tulsa it is 27 C and in Juneau it is 4 C. Now it looks like Tulsa is 4 times as hot as Juneau! Yet Fahrenheit and Centigrade are perfectly equivalent and equally valid measuring scales. So you know ratios are not meaningful in interval measurement. 2. The ratios of differences (intervals) among measured values is meaningful. For example, suppose it is 70 F in L.A. and 50 F in San Francisco. The difference in temperature between Tulsa and Juneau (40 F) is twice as much as the difference in temperature between L.A. and San Francisco (20 F). This statement is still true if we measure the temperatures in Centigrade, so interval measurements preserve ratios of differences in measured values. |
| Glossary V2.0 | |
Contoh Jabaran Variabel Penelitian, Sub Variabel dan Indikator Penelitian (16992)
Thesis: Action Research Tutorial (6451)