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| Robuszt kvantitatív tartalomelemzés× | Leíró kutatás – Leíró kutatási terv× | |
|---|---|---|
| Tudományterület | Kutatástervezés | Kutatástervezés |
| Módszercsalád | Process / pipeline | Process / pipeline |
| Keletkezés éve≠ | 1980s–2000s (systematic application of robust statistics to content analysis) | Late 19th century; formalized in social/behavioral sciences ~1960s–1980s |
| Megalkotó≠ | Klaus Krippendorff; Kimberly Neuendorf (systematic codification); robust statistics tradition from Peter Huber (1964) | Francis Galton, Karl Pearson (early empirical tradition); formalized in social science by Fred Kerlinger |
| Típus≠ | Quantitative research design with robust statistical estimation | Non-experimental quantitative research design |
| Alapmű≠ | Neuendorf, K. A. (2002). The Content Analysis Guidebook. Sage Publications. ISBN: 978-0761919773 | Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage. ISBN: 978-1452226101 |
| Alternatív nevek | robust content analysis, outlier-resistant content analysis, robust QCA, robust text frequency analysis | descriptive study, descriptive survey design, observational descriptive research, non-experimental descriptive research |
| Kapcsolódó≠ | 4 | 3 |
| Összefoglaló≠ | Robust quantitative content analysis is a systematic method for coding and counting manifest or latent features of communication content — texts, images, or media — while applying statistical estimators that are resistant to outliers, skewed distributions, and coding inconsistencies. By combining the structured coding protocol of classical content analysis with robust statistical measures, it produces frequency and association estimates that are less distorted when data violate normality assumptions or contain extreme values. | Descriptive research is a non-experimental quantitative design that systematically documents the characteristics, frequencies, or distributions of variables in a defined population at a given point in time. It answers 'what is' questions — who, what, when, where, and how much — without manipulating variables or drawing causal conclusions. It is one of the most widely used research designs across the social, behavioral, health, and education sciences. |
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