Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Prueba z para dos proporciones× | Prueba t para muestras independientes× | |
|---|---|---|
| Campo | Estadística | Estadística |
| Familia | Hypothesis test | Hypothesis test |
| Año de origen≠ | 1900 | 1908 |
| Autor original≠ | Karl Pearson / classical large-sample z approximation | Student (W. S. Gosset) |
| Tipo≠ | Parametric proportion comparison | Parametric mean comparison |
| Fuente seminal≠ | Fleiss, J. L., Levin, B., & Paik, M. C. (2003). Statistical Methods for Rates and Proportions (3rd ed.). Wiley. DOI ↗ | Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗ |
| Alias | z-test for proportions, two-sample proportion test, one-proportion z-test, Oran Testi — z Testi (Oranlar) | student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi |
| Relacionados | 4 | 4 |
| Resumen≠ | 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. | The independent samples t-test is a parametric hypothesis test that compares the means of two independent groups to decide whether they differ significantly. It builds on the t-distribution introduced by Student (W. S. Gosset) in 1908 and assumes the measured values are continuous, approximately normally distributed, and have equal variances. |
| ScholarGateConjunto de datos ↗ |
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