Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Многовариантно изследователско количествено изследване× | Експлораторно количествено изследване× | |
|---|---|---|
| Област | Дизайн на изследването | Дизайн на изследването |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1930s–1960s (foundational multivariate methods); codified in research design literature from the 1980s onward | Mid-20th century (codified in social research methods texts c. 1950s–1970s) |
| Създател≠ | Hair, Tabachnick, and colleagues (canonical synthesis); roots in Fisher, Hotelling, and Thurstone (early 20th century) | Earl Babbie; John Creswell (systematic codification in social science methods) |
| Тип≠ | Quantitative research design | Non-experimental quantitative research design |
| Основополагащ източник≠ | Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540 | Babbie, E. (2021). The Practice of Social Research (15th ed.). Cengage Learning. ISBN: 978-0357360767 |
| Други названия | multivariate exploratory design, exploratory multivariate analysis, multivariate data exploration, MEQ research | quantitative exploratory design, exploratory survey research, initial quantitative investigation, preliminary quantitative study |
| Свързани≠ | 5 | 4 |
| Резюме≠ | Multivariate exploratory quantitative research is a design in which researchers simultaneously examine multiple quantitative variables without imposing a predetermined structural model, using techniques such as exploratory factor analysis, cluster analysis, or principal component analysis to detect latent patterns, natural groupings, or underlying dimensions in the data. The goal is discovery and pattern recognition rather than hypothesis confirmation. | Exploratory quantitative research is a non-experimental design used when a phenomenon is insufficiently understood to support formal hypothesis testing. The researcher collects numerical data — typically through surveys, structured observation, or existing records — to describe distributions, detect patterns, and generate hypotheses that more targeted confirmatory studies can subsequently test. It occupies the first stage of a cumulative quantitative research programme. |
| ScholarGateНабор от данни ↗ |
|
|