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Regression model

Msawazo Mkuu wa Mlinganyo (MLR)

Msawazo mkuu wa mlinganyo (MLR) ni modeli sanifu ya kurudi nyuma (regression) inayoelezea matokeo yanayoendelea (continuous outcome) kama mchanganyiko wa mstari wenye uzito wa vigezo mtafiti viwili au zaidi pamoja na kosa la nasibu. Uzito usiokuwa na uhakika (vigawo vya kurudi nyuma) hutathminiwa kwa njia ya viwango vidogo zaidi vya makosa (ordinary least squares - OLS), ambayo hupunguza jumla ya mabaki yaliyopimwa. Njia hii inatokana na kazi ya Francis Galton ya mwaka 1886 kuhusu urithi wa kimo na iliwekwa kwa msingi imara wa hisabati na Karl Pearson; kitabu cha Draper na Smith cha mwaka 1966 kilikithibitisha kama mfumo sanifu wa kurudi nyuma kwa vitendo.

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Vyanzo

  1. Galton, F. (1886). Regression towards mediocrity in hereditary stature. Journal of the Anthropological Institute of Great Britain and Ireland, 15, 246–263. DOI: 10.2307/2841583
  2. Pearson, K., & Lee, A. (1908). On the generalised probable error in multiple normal correlation. Biometrika, 6(1), 59–68. DOI: 10.1093/biomet/6.1.59
  3. Draper, N. R., & Smith, H. (1966). Applied Regression Analysis (1st ed.). John Wiley & Sons. ISBN: 9780471221708
  4. Montgomery, D. C., Peck, E. A., & Vining, G. G. (2012). Introduction to Linear Regression Analysis (5th ed.). John Wiley & Sons. ISBN: 9780470542811

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Multiple Linear Regression (Ordinary Least Squares). ScholarGate. https://scholargate.app/sw/statistics/multiple-linear-regression

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ScholarGateMultiple Linear Regression (Multiple Linear Regression (Ordinary Least Squares)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/statistics/multiple-linear-regression · Seti ya data: https://doi.org/10.5281/zenodo.20539026