Glossary | |
| These is glossary of research key terms. | |
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| Term | Definition |
| Sampel | Pendapat Sugiyono, sampel adalah bagian dari jumlah dan karakteristik yang dimiliki oleh populasi tersebut. Contoh: Karena jumlah populasi tidak diketahui tidak terhingga, maka jumlah penentuan sampel dilakukan berdasarkan pendapat Nares K. Malhotru (1993:622), yang menyatakan bahwa jumlah sampel atau responden paling sedikit empat atau lima kali jumlah sub variabel/item yang digunakan dalam penelitian.
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| Sample | 1. A subset of population elements. In some usages, contrasts with population. 2. a selection of units from a population (universe). Of particular importance is how the sample was selected (see simple random sample [SRS]). 3. subset of the population used for study. |
| Sampling | 1. The practice of choosing a subset of population elements to study instead of the entire population. In general, we sample because (a) it's cheaper; (b) in some cases the population is theoretically infinite. There are two basic kinds of sampling: probability and non-probability. 2. The process of selecting a subgroup of a population to represent the entire population. There are several different types of sampling, including: |
| Sampling bias | Distortion that occurs when a sample is not representative of the population from which it was drawn. |
| Sampling Error | 1. A difference, due to sampling, between a population parameter and the corresponding sample statistic. For example, the average age of a population might be 25 years, but a given sample might yield an average of 26 because, by chance, more old people were selected than the population proportion. 2. The fluctuation in the value of a statistic from different samples drawn from the same population. 3. Random or unsystematic error resulting from selecting a sample from a population. 4. the error in estimates of a population due to the variation possible in samples |
| Sampling Frame | 1. The sampling frame is a specific list of names (or other identifying codes) of the cases to be sampled. Usually, this is supposed to be the same as the population. For example, when you study IBM, you start by obtaining a list of all IBM employees. This is the sampling frame. If your list is not complete (e.g., it omits top management), your results may not be valid in the sense of generalizing to all of IBM. 2. A list of the entire population eligible to be included within the specific parameters of a research study. A researcher must have a sampling frame in order to generate a random sample. |
| Sampling Ratio | The sampling ratio is the size of the sample divided by the size of the population. |
| Scale | composite measures of variables that form a pattern logical/or empirical. Scores thus indicate a pattern not just a sum of component variables, e.g. Bogardus social distance scale. |
| Scientific laws | Generalized laws that are always true and can be used to predict future events. |
| Scientism | Knowing how to investigate without any understanding of what it is. |
| Secondary analysis | a form of research where data collected by others, researchers, government agencies or organizations for their own purposes is used for a different research purpose e.g. the officially collected census and criminal justice data used in this module for research purposes. |
| Secondary data analysis | A research method where data collected by one researcher is reanalyzed by another researcher for either different or the same purpose. |
| Semiology or Semiotics | The science of signs and symbols |
| Significance (statistical) | 1. Refers to the probability that an occurrence, a relationship or a distribution did not occur by chance, was not due to sampling error (obtaining an unusual, non typical sample). A test of significance determines the probability a relationship or distribution is real and not due to chance. See significance (substantive) for popular usage. 2. the likelihood that a table distribution, a relationship, etc. could have occurred by chance. |
| Significance (substantive) | Refers to the socially defined importance of a finding e.g. |
| Glossary V2.0 | |
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Disciplines discipline knowledge: (1) making claims liable for adjudication, (2) producing expertise, and (3) defining truth. (Robert Frodeman and Carl Mitcham) |