Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uchambuzi wa Nguvu kwa Regresheni Nyingi× | Uchambuzi wa Nguvu za Kimahesabu kwa Uhusiano wa Pearson× | |
|---|---|---|
| Nyanja | Takwimu | Takwimu |
| Familia | Hypothesis test | Hypothesis test |
| Mwaka wa asili | 1988 | 1988 |
| Mwanzilishi | Jacob Cohen | Jacob Cohen |
| Aina≠ | A priori sample size determination | Sample size / power 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≠ | regression power analysis, sample size estimation regression, f² power analysis, Güç Analizi — Regresyon | Korelasyon Güç Analizi, power analysis for r, sample size for correlation |
| Zinazohusiana | 4 | 4 |
| Muhtasari≠ | Power analysis for multiple regression is a pre-study procedure, formalised by Jacob Cohen (1988), that calculates the minimum sample size needed to detect a regression effect of a given size with adequate statistical power. It uses the anticipated R² (or the equivalent Cohen's f² effect size) and the number of predictors to determine how many observations must be collected before data collection begins. | 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. |
| ScholarGateSeti ya data ↗ |
|
|