Hypothesis testClassical statistics

Robustnost jednovarijantnog t-testa (trimmed mean)

Robusni jednovarijantni t-test zamenjuje običan aritmetičku sredinu trimmed mean-om (ošišanim prosekom) i uzorak varijanse Winsorized varijansom kako bi se lokacija populacije uporedila sa hipoteziranom vrednošću. Zadržava okvir odlučivanja t-testa, istovremeno oštro smanjujući osetljivost na ekstremne vrednosti (outliers) i distribucije sa teškim repovima, čineći ga pouzdanim za stvarne neprekidne podatke koji odstupaju od normalnosti.

Primenite uz StatMindUskoroVideoUskoroDownload slides

Pročitajte celu metodu

Samo za članove

Prijavite se besplatnim nalogom da biste pročitali ovaj odeljak.

Prijavite se

Method map

The neighbourhood of related methods — select a node to explore.

Izvori

  1. Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838
  2. Yuen, K. K. (1974). The two-sample trimmed t for unequal population variances. Biometrika, 61(1), 165–170. DOI: 10.1093/biomet/61.1.165

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Robust One-Sample Location Test Using Trimmed Mean. ScholarGate. https://scholargate.app/sr/statistics/robust-one-sample-t-test

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side

Citirana u

ScholarGateRobust one-sample t-test (Robust One-Sample Location Test Using Trimmed Mean). Preuzeto 2026-06-15 sa https://scholargate.app/sr/statistics/robust-one-sample-t-test · Skup podataka: https://doi.org/10.5281/zenodo.20539026