Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Utafiti wa Kianaliti wa Msalaba× | Utafiti wa Utafiti× | |
|---|---|---|
| Nyanja | Muundo wa Utafiti | Muundo wa Utafiti |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1960s–1970s (formalized with widespread multivariate methods) | Late 19th century; methodologically systematised 1940s–1960s |
| Mwanzilishi≠ | Developed from the convergence of survey methodology (Kerlinger) and multivariate statistics (Tabachnick, Fidell) | Francis Galton, Charles Booth, and early social statisticians; systematised by Paul Lazarsfeld and colleagues at Columbia in the 1940s |
| Aina≠ | Quantitative observational design | Quantitative (and mixed) non-experimental design |
| Chanzo asilia≠ | Kerlinger, F. N., & Lee, H. B. (2000). Foundations of Behavioral Research (4th ed.). Harcourt College Publishers. ISBN: 978-0155078970 | Fowler, F. J. (2014). Survey Research Methods (5th ed.). Sage Publications. ISBN: 978-1452259000 |
| Majina mbadala | multivariate survey design, multi-variable cross-sectional study, MXSR, multivariate observational study | survey methodology, questionnaire research, survey design, survey study |
| Zinazohusiana≠ | 3 | 4 |
| Muhtasari≠ | Multivariate cross-sectional research collects data on multiple variables from a defined population at a single point in time and uses multivariate statistical techniques — such as multiple regression, MANOVA, factor analysis, or structural equation modeling — to examine simultaneous relationships among those variables. It combines the efficiency of a cross-sectional snapshot with the analytical power to handle complex, multi-variable research questions in a single study. | Survey research is a quantitative (and sometimes mixed-methods) design in which a researcher collects standardised self-report data from a sample drawn from a defined population, using a questionnaire or structured interview. It is the dominant non-experimental strategy for describing population characteristics, estimating prevalence, mapping attitude distributions, and testing bivariate or multivariate associations across social, behavioural, and health sciences. |
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