Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Takwimu Elekezi Imara× | Uchambuzi wa Nguvu× | |
|---|---|---|
| Nyanja | Takwimu | Takwimu |
| Familia | Hypothesis test | Hypothesis test |
| Mwaka wa asili≠ | 1960s–1970s | 1969 (1st ed.); 1988 (seminal 2nd ed.) |
| Mwanzilishi≠ | John W. Tukey, Peter J. Huber, Frank Hampel | Jacob Cohen |
| Aina≠ | Resistant summary measures | Sample size and power planning |
| Chanzo asilia≠ | Tukey, J. W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165 | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 |
| Majina mbadala | resistant statistics, outlier-resistant summary statistics, robust summary measures, robust location and scale estimation | sample size calculation, power calculation, sensitivity analysis, a priori power analysis |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | Robust descriptive statistics summarize the location, spread, and shape of a dataset using measures that remain meaningful even when a fraction of the data contains outliers or severe departures from normality. Core tools include the median, trimmed mean, interquartile range (IQR), and median absolute deviation (MAD), all of which are resistant to contamination that would distort the classic mean and standard deviation. | Power analysis is a planning and evaluation technique that quantifies the probability of detecting a real effect of a given magnitude at a chosen significance level. It links four quantities — sample size, effect size, significance level (alpha), and statistical power (1 minus beta) — so that researchers can determine the sample size needed before data collection or evaluate the sensitivity of a completed study. |
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