Vertaile menetelmiä

	Kahden osuuden z-testi	Logistinen regressio
Tieteenala	Tilastotiede	Tutkimuksen tilastomenetelmät
Menetelmäperhe	Hypothesis test	Process / pipeline
Syntyvuosi	1900	1958
Kehittäjä	Karl Pearson / classical large-sample z approximation	David Roxbee Cox
Tyyppi	Parametric proportion comparison	Method
Alkuperäislähde	Fleiss, J. L., Levin, B., & Paik, M. C. (2003). Statistical Methods for Rates and Proportions (3rd ed.). Wiley.	Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.
Rinnakkaisnimet	z-test for proportions, two-sample proportion test, one-proportion z-test, Oran Testi — z Testi (Oranlar)	logit model, binomial logistic regression, LR
Liittyvät	4	3
Tiivistelmä	The proportion test (z-test for proportions) is a parametric hypothesis test that compares one or two sample proportions against a reference value or each other. Grounded in the large-sample normal approximation formalized by Fleiss, Levin, and Paik (2003), it is the standard tool for binary outcome comparisons when samples are large enough for the central limit theorem to apply.	Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.