Comparar métodos

	Pesquisa Explicativa	Pesquisa de Teste de Hipóteses
Área	Delineamento de pesquisa	Delineamento de pesquisa
Família	Process / pipeline	Process / pipeline
Ano de origem	1960s–1980s (codified in behavioral and social science methodology)	Early 20th century (Fisher 1925; Neyman–Pearson 1933)
Autor original	Formalized by Earl Babbie and Fred Kerlinger among others	Karl Pearson, Ronald A. Fisher, Jerzy Neyman, Egon Pearson
Tipo	Non-experimental quantitative research design	Quantitative confirmatory research design
Fonte seminal	Kerlinger, F. N. (1986). Foundations of Behavioral Research (3rd ed.). Holt, Rinehart and Winston. ISBN: 978-0030417559	Kerlinger, F. N., & Lee, H. B. (1986). Foundations of Behavioral Research (3rd ed.). Holt, Rinehart and Winston. ISBN: 978-0030417603
Outros nomes	analytical research, causal research, explanatory study, explanatory quantitative research	hypothetico-deductive research, confirmatory quantitative research, null hypothesis significance testing, NHST design
Relacionados	5	4
Resumo	Explanatory research is a non-experimental quantitative research design that goes beyond describing a phenomenon to identifying why it occurs — examining the relationships or mechanisms that account for observed patterns. Rooted in positivist social science methodology, it uses theory-driven hypotheses and statistical analysis to test whether specific variables explain variation in an outcome, without necessarily manipulating those variables.	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.