Salīdzināt metodes

	Jaudas analīze t-testam	Velča t-tests (nevienādas dispersijas)
Nozare	Statistika	Statistika
Saime	Hypothesis test	Hypothesis test
Izcelsmes gads	1969	1947
Autors	Jacob Cohen	B. L. Welch
Tips	Sample size determination	Parametric mean comparison (unequal variances)
Pirmavots	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832	Welch, B. L. (1947). The generalization of Student's problem when several different population variances are involved. Biometrika, 34(1/2), 28–35.
Citi nosaukumi	t-test power analysis, sample size calculation for t-test, Güç Analizi — t-Testi	unequal variances t-test, Welch-Satterthwaite t-test, Welch t-Testi (Eşit Olmayan Varyans)
Saistītās	5	4
Kopsavilkums	Power analysis for the t-test is a sample size planning procedure that determines how many participants are required to detect a mean difference of a given magnitude with acceptable probability. Formalised by Jacob Cohen in his 1969 and 1988 editions of Statistical Power Analysis for the Behavioral Sciences, it links four quantities — effect size (Cohen's d), significance level (α), statistical power (1 − β), and sample size — so that fixing any three allows calculation of the fourth.	Welch's t-test is a parametric hypothesis test that compares the means of two independent groups without assuming their variances are equal. It was introduced by B. L. Welch in 1947 as a more robust generalization of Student's two-sample test for situations where the two groups have different spread.