Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uchambuzi wa Nguvu za Kimahesabu kwa Uhusiano wa Pearson× | Uchambuzi wa Nguvu kwa ANOVA× | |
|---|---|---|
| Nyanja | Takwimu | Takwimu |
| Familia | Hypothesis test | Hypothesis test |
| Mwaka wa asili | 1988 | 1988 |
| Mwanzilishi | Jacob Cohen | Jacob Cohen |
| Aina≠ | Sample size / power determination | Sample size determination |
| Chanzo asilia | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 |
| Majina mbadala≠ | Korelasyon Güç Analizi, power analysis for r, sample size for correlation | ANOVA power analysis, F-test power analysis, sample size for ANOVA, Güç Analizi — ANOVA |
| Zinazohusiana | 4 | 4 |
| Muhtasari≠ | Correlation power analysis is a pre-study calculation that determines how many participants are needed — or how much statistical power an existing sample provides — for a Pearson correlation test. Formalised by Jacob Cohen in his landmark 1988 text, it uses the expected correlation coefficient r directly as the effect size, so researchers can plan studies that are neither underpowered nor wastefully large. | Power analysis for ANOVA is a prospective statistical technique that determines the minimum sample size needed to detect a specified group mean difference with a chosen probability. Formalized by Jacob Cohen in his 1988 monograph, it translates a researcher's effect size expectation — expressed as Cohen's f — along with the desired Type I error rate (alpha) and statistical power (1 − beta) into a concrete per-group sample size recommendation for one-way or factorial ANOVA designs. |
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