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| Hierarkisk eksplorativ kvantitativ forskning× | Klyngeudvælgelse× | |
|---|---|---|
| Fagområde≠ | Forskningsdesign | Surveymetodologi |
| Familie | Process / pipeline | Process / pipeline |
| Oprindelsesår≠ | mid-20th century onward | Early-to-mid 20th century; canonical treatment 1953/1977 |
| Ophavsperson≠ | Developed from survey research traditions (Kish, 1965; Babbie, 1990s) | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice |
| Type≠ | Quantitative observational and survey design | Probability sampling design |
| Oprindelig kilde≠ | Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage Publications. ISBN: 978-1452226101 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 |
| Aliasser≠ | stratified exploratory survey design, hierarchical survey research, multilevel exploratory quantitative design, hierarchical descriptive-quantitative design | cluster random sampling, area sampling, one-stage cluster sampling |
| Relaterede≠ | 2 | 5 |
| Resumé≠ | Hierarchical exploratory quantitative research is a survey and observational design that structures both sampling and analysis across nested population levels — such as students within classrooms within schools — to explore patterns, distributions, and relationships in numerical data without a pre-specified directional hypothesis. It is oriented toward discovery and description rather than confirmation, making it appropriate early in a research programme when the phenomenon is not yet well-mapped. | Cluster sampling is a probability sampling technique in which the population is divided into naturally occurring groups (clusters), a random sample of clusters is selected, and all — or a random subset of — members within each selected cluster are studied. It is especially practical when a complete population list is unavailable or when units are geographically dispersed, making individual random selection prohibitively expensive. One-stage cluster sampling surveys every member of selected clusters; two-stage designs add a second random draw within clusters. |
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