Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Análise de Poder para o teste t× | Teste t para amostras pareadas× | |
|---|---|---|
| Área | Estatística | Estatística |
| Família | Hypothesis test | Hypothesis test |
| Ano de origem≠ | 1969 | 1908 |
| Autor original≠ | Jacob Cohen | Student (W. S. Gosset) |
| Tipo≠ | Sample size determination | Parametric mean comparison (paired) |
| Fonte seminal≠ | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 | Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed.). SAGE. ISBN: 978-1446249185 |
| Outros nomes≠ | t-test power analysis, sample size calculation for t-test, Güç Analizi — t-Testi | dependent samples t-test, repeated measures t-test, matched-pairs t-test, eşleştirilmiş örneklem t-testi |
| Relacionados≠ | 5 | 4 |
| Resumo≠ | 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. | The paired samples t-test is a parametric hypothesis test that compares two measurements taken on the same subjects — such as a before and after reading — to decide whether the average change differs from zero. It rests on the t-distribution introduced by Student (W. S. Gosset) in 1908 and works on the within-subject difference scores rather than the raw measurements. |
| ScholarGateConjunto de dados ↗ |
|
|