পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| একাধিক রিগ্রেশনের জন্য পাওয়ার বিশ্লেষণ× | বহুচলক রৈখিক নির্ভরণ× | |
|---|---|---|
| ক্ষেত্র | পরিসংখ্যান | পরিসংখ্যান |
| পরিবার≠ | Hypothesis test | Regression model |
| উদ্ভবের বছর≠ | 1988 | 1886 |
| প্রবর্তক≠ | Jacob Cohen | Francis Galton; formalized by Karl Pearson |
| ধরন≠ | A priori sample size determination | Parametric linear model |
| মৌলিক উৎস≠ | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 | Galton, F. (1886). Regression towards mediocrity in hereditary stature. Journal of the Anthropological Institute of Great Britain and Ireland, 15, 246–263. DOI ↗ |
| অপর নাম≠ | regression power analysis, sample size estimation regression, f² power analysis, Güç Analizi — Regresyon | MLR, OLS regression, multiple regression, linear regression with multiple predictors |
| সম্পর্কিত≠ | 4 | 8 |
| সারসংক্ষেপ≠ | 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. | Multiple linear regression (MLR) is a parametric regression model that expresses a continuous outcome as a weighted linear combination of two or more predictor variables plus a random error term. The unknown weights (regression coefficients) are estimated by ordinary least squares (OLS), which minimises the sum of squared residuals. The method traces to Francis Galton's 1886 work on hereditary stature and was placed on firm mathematical footing by Karl Pearson; Draper and Smith's 1966 textbook established it as the standard framework for applied regression. |
| ScholarGateডেটাসেট ↗ |
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