Compara mètodes

	Interval de Confiança	Proves d'Hipòtesi Nul·la
Camp	Estadística per a la recerca	Estadística per a la recerca
Família	Process / pipeline	Process / pipeline
Any d'origen	1937	1925
Autor original	Jerzy Neyman	Ronald Fisher; Neyman & Pearson
Tipus	Concept	Concept
Font seminal	Neyman, J. (1937). Outline of a Theory of Statistical Estimation Based on the Classical Theory of Probability. Philosophical Transactions of the Royal Society, 236, 333–380.	Fisher, R. A. (1925). Statistical Methods for Research Workers. Oliver and Boyd.
Àlies	CI, 95% CI, credible interval, interval estimate	NHST, hypothesis formulation, null hypothesis, alternative hypothesis
Relacionats	4	4
Resum	A confidence interval (CI) is a range of values, calculated from sample data, that likely contains the true population parameter. Introduced by Jerzy Neyman in 1937, it provides an interval estimate rather than a single point estimate, incorporating both the observed value and the uncertainty around it. The standard 95% confidence interval is a robust, intuitive alternative to p-values for communicating research results.	Null Hypothesis Significance Testing (NHST) is the dominant statistical framework in empirical research. The null hypothesis (H₀) represents the default assumption—typically 'no effect' or 'no difference'—while the alternative hypothesis (H₁) represents the claim being tested. The test calculates the probability of observing the data given H₀ is true (p-value); if p is very small, H₀ is rejected in favor of H₁. Formulated by Ronald Fisher and extended by Neyman and Pearson in the early 20th century, NHST is foundational to confirmatory research but has been widely critiqued for misuse and misinterpretation.