REGRESSIYA TAHLILI EHTIMOLLIK VA STATISTIKADA BASHORAT QILISH USULI SIFATIDA

Аннотация

Ushbu maqolada regressiya tahlilining ehtimollik va statistika sohasidagi ahamiyati, qo‘llanilishi va turli shakllari atroflicha tahlil qilinadi. Regressiya usullarining tarixiy rivojlanishi, ularning chiziqli, logistik, chiziqli bo‘lmagan hamda zamonaviy metodologiyalar bilan uyg‘unlashgan holatlari keng yoritilgan. Ayniqsa, moliya, energetika, sog‘liqni saqlash, meteorologiya va matn tahlili kabi sohalarda regressiyaning amaliy qo‘llanilishi bo‘yicha real tadqiqotlar misolida batafsil tushuntirishlar keltirilgan. Tahlil davomida ARIMAX, SARIMAX, Bayesian, FAR kabi ilg‘or modellarning afzalliklari va bashoratlashdagi aniqligi alohida ta’kidlanadi. Maqola regressiya tahlilining ilmiy va amaliy sohalardagi hal qiluvchi o‘rni, uning yordamida ma’lumotlar asosida asosli qarorlar qabul qilish imkoniyatlarini yoritib beradi. Kalit so‘zlar: Regressiya tahlili, ehtimollar nazariyasi, statistik modellashtirish, chiziqli regressiya, logistik regressiya, vaqtli qatorlar, ARIMA, SARIMAX, Bayes regressiyasi, bashorat qilish, ma’lumotlar tahlili. Annotation: This article provides an in-depth analysis of the importance, application, and various forms of regression analysis within the field of probability and statistics. It explores the historical development of regression methods and their integration with both traditional and modern methodologies, including linear, logistic, and nonlinear models. Particular attention is given to practical applications in fields such as finance, energy, healthcare, meteorology, and text analysis, supported by real-life research examples. Advanced models such as ARIMAX, SARIMAX, Bayesian, and FAR are discussed, highlighting their advantages and accuracy in forecasting. The article emphasizes the critical role of regression analysis in scientific and practical domains, enabling data-driven and evidence-based decision-making. 79 International scientific journal “Interpretation and researches” Volume 1 issue 7 (53) | ISSN: 2181-4163 | Impact Factor: 8.2 Keywords: Regression analysis, probability theory, statistical modeling, linear regression, logistic regression, time series, ARIMA, SARIMAX, Bayesian regression, forecasting, data analysis.