Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Kipimo kamili cha Binomial× | Uchambuzi wa Nguvu kwa ANOVA× | |
|---|---|---|
| Nyanja | Takwimu | Takwimu |
| Familia≠ | Regression model | Hypothesis test |
| Mwaka wa asili | 1988 | 1988 |
| Mwanzilishi≠ | Classical exact test; textbook treatment by Siegel & Castellan | Jacob Cohen |
| Aina≠ | Exact one-sample test for a proportion | Sample size determination |
| Chanzo asilia≠ | Siegel, S. & Castellan, N. J. (1988). Nonparametric Statistics for the Behavioral Sciences (2nd ed.). McGraw-Hill. ISBN: 978-0070573574 | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 |
| Majina mbadala | exact binomial test, binomial probability test, exact test for a proportion, Tam Binom Testi | ANOVA power analysis, F-test power analysis, sample size for ANOVA, Güç Analizi — ANOVA |
| Zinazohusiana≠ | 2 | 4 |
| Muhtasari≠ | The exact binomial test checks whether the observed number of successes in a fixed number of independent trials is consistent with a pre-specified success probability p₀. Because it computes exact binomial tail probabilities rather than relying on a normal approximation, it is the gold standard for testing a proportion in small samples; this two-sided formulation follows Siegel & Castellan's classic treatment (1988). | 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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