Linganisha mbinu

	Kipimo kamili cha Binomial	Kipimo cha idadi-mbili cha z
Nyanja	Takwimu	Takwimu
Familia	Regression model	Hypothesis test
Mwaka wa asili	1988	1900
Mwanzilishi	Classical exact test; textbook treatment by Siegel & Castellan	Karl Pearson / classical large-sample z approximation
Aina	Exact one-sample test for a proportion	Parametric proportion comparison
Chanzo asilia	Siegel, S. & Castellan, N. J. (1988). Nonparametric Statistics for the Behavioral Sciences (2nd ed.). McGraw-Hill. ISBN: 978-0070573574	Fleiss, J. L., Levin, B., & Paik, M. C. (2003). Statistical Methods for Rates and Proportions (3rd ed.). Wiley.
Majina mbadala	exact binomial test, binomial probability test, exact test for a proportion, Tam Binom Testi	z-test for proportions, two-sample proportion test, one-proportion z-test, Oran Testi — z Testi (Oranlar)
Zinazohusiana	2	4
Muhtasari	The exact binomial test checks whether the observed number of successes in a fixed number of independent trials is consistent with a pre-specified success probability p₀. Because it computes exact binomial tail probabilities rather than relying on a normal approximation, it is the gold standard for testing a proportion in small samples; this two-sided formulation follows Siegel & Castellan's classic treatment (1988).	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.