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HUDUDIY RIVOJLANISHNING INTEGRAL INDEKSINI QURISHDAINDIKATORLARNI TANLASHNING STATISTIK USULLARI:KORRELYATSIYA, FAKTOR VA KLASTER TAHLILI ASOSIDA QIYOSIYTAHLIL

Nashr etilgan 2026-04-07

Mualliflar
Sattorov Sanjar Abdumurodovich
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Annotatsiya

Ushbu maqolada hududiy rivojlanishning integral indeksini shakllantirishda
qoʻllaniladigan uchta statistik usul — korrelyatsiya, faktor va klaster tahlili — qiyosiy
tarzda oʻrganildi. Xalqaro composite indekslar metodologiyasiga oid yondashuvlar
tadqiq qilinib, indikatorlarni tanlashda obyektivlikni taʼminlovchi bosqichli algoritm
ishlab chiqildi. Surxondaryo viloyatining 2010-2024 yillarga oid rasmiy statistik
maʼlumotlari asosida usullarning qoʻllanilish imkoniyatlari taqqoslandi. Korrelyatsiya
tahlili 12 indikatordan 7 tasini saralab chiqdi; faktor tahlili iqtisodiy-taʼlim va sogʻliqni
saqlash latent omillarini aniqlandi. Klaster tahlili 15 hududni 3 ta aniq guruhga ajratdi.
Kombinatsion yondashuv monitoring tizimida eng yuqori diagnostik quvvatni
taʼminlashi isbotlandi. Natijalarga asoslangan tavsiyalar davlat statistika organlari
uchun amaliy qiymat kasb etadi.

Kalit so'zlar

integral indeks, hududiy rivojlanish, korrelyatsiya tahlili, faktor tahlili, klaster tahlili, indikatorlar tanlash.

Adabiyotlar ro'yxati

  1. 1. UNDP. Human Development Report 2023/2024: Breaking the Gridlock:
  2. Reimagining Cooperation in a Polarized World. New York: UNDP, 2023. URL:
  3. https://hdr.undp.org/content/human-development-report-2023-24
  4. 2. UNDP. Human Development Report 1990: Concept and Measurement of
  5. Human Development. New York: UNDP, 1990. URL:
  6. https://hdr.undp.org/content/human-development-report-1990
  7. 3. OECD/JRC. Handbook on Constructing Composite Indicators: Methodology
  8. and User Guide. Paris: OECD Publishing, 2008. DOI:
  9. https://doi.org/10.1787/9789264043466-en
  10. 4. Freudenberg M. Composite indicators of country performance: A critical
  11. assessment. OECD Science, Technology and Industry Working Papers 2003/16. DOI:
  12. https://doi.org/10.1787/405566708255
  13. 5. Greco S., Ishizaka A., Tasiou M., Torrisi G. On the methodological framework
  14. of composite indices: A review of the issues of weighting, aggregation, and robustness. Social Indicators Research, 2019, 141(1): 61-94. DOI: https://doi.org/10.1007/s11205-017-1832-9
  15. 6. Jolliffe I.T., Cadima J. Principal component analysis: a review and recent
  16. developments. Philosophical Transactions of the Royal Society A, 2016, 374(2065).DOI: https://doi.org/10.1098/rsta.2015.0202
  17. 7. Ward J.H. Hierarchical grouping to optimize an objective function. Journal of
  18. the American Statistical Association, 1963, 58(301): 236-244. DOI:
  19. https://doi.org/10.1080/01621459.1963.10500845
  20. 8. Hair J.F., Black W.C., Babin B.J., Anderson R.E. Multivariate Data Analysis
  21. (8th ed.). Cengage Learning, 2019. DOI: https://doi.org/10.1002/9781119409137
  22. 9. Kaiser H.F. The application of electronic computers to factor analysis.
  23. Educational and Psychological Measurement, 1960, 20(1): 141-151. DOI:
  24. https://doi.org/10.1177/001316446002000109
  25. 10. European Commission. Regional Competitiveness Index 2022. Brussels: EC,
  26. 2022. URL: https://ec.europa.eu/regional_policy/information-sources/maps/regionalcompetitiveness_en

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