Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Investigación por contraste de hipótesis× | Investigación Confirmatoria× | |
|---|---|---|
| Campo | Diseño de investigación | Diseño de investigación |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | Early 20th century (Fisher 1925; Neyman–Pearson 1933) | 1934 (Popper); widely adopted in social sciences from 1960s onward |
| Autor original≠ | Karl Pearson, Ronald A. Fisher, Jerzy Neyman, Egon Pearson | Karl Popper (falsificationism); formalized in behavioral sciences by Paul Meehl and others |
| Tipo≠ | Quantitative confirmatory research design | Quantitative research design |
| Fuente seminal≠ | Kerlinger, F. N., & Lee, H. B. (1986). Foundations of Behavioral Research (3rd ed.). Holt, Rinehart and Winston. ISBN: 978-0030417603 | Popper, K. R. (1959). The Logic of Scientific Discovery. Hutchinson. ISBN: 978-0415278447 |
| Alias | hypothetico-deductive research, confirmatory quantitative research, null hypothesis significance testing, NHST design | hypothesis-testing research, deductive research, theory-testing research, confirmatory study |
| Relacionados | 4 | 4 |
| Resumen≠ | Hypothesis testing research is a quantitative design in which the investigator derives one or more explicit, falsifiable propositions from theory, translates them into a null hypothesis (H0) and an alternative hypothesis (H1), collects empirical data, and then applies an inferential statistical test to decide whether the evidence is sufficient to reject H0. The approach is the dominant paradigm for confirmatory science across the social, behavioral, health, and natural sciences. | Confirmatory research is a deductive quantitative design in which the researcher specifies hypotheses derived from existing theory before data collection, then tests whether the data support or refute those hypotheses. Unlike exploratory approaches that generate ideas from data, confirmatory research begins with an established theoretical framework, pre-registers predictions, and applies statistical tests to evaluate those predictions against empirical evidence. It is the backbone of hypothesis-driven social, behavioral, and health science inquiry. |
| ScholarGateConjunto de datos ↗ |
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