ekonometrik modellar parametrlarini baholash

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youts/_rels/slidelayout2.xml.rels ppt/slidelayouts/_rels/slidelayout3.xml.rels ppt/slidelayouts/_rels/slidelayout4.xml.rels ppt/slidelayouts/_rels/slidelayout5.xml.rels ppt/slidelayouts/_rels/slidelayout6.xml.rels ppt/slidelayouts/_rels/slidelayout7.xml.rels ppt/slidelayouts/_rels/slidelayout8.xml.rels ppt/slidelayouts/_rels/slidelayout9.xml.rels ppt/slidemasters/_rels/slidemaster1.xml.rels ppt/slides/_rels/slide1.xml.rels ppt/slides/_rels/slide10.xml.rels ppt/slides/_rels/slide11.xml.rels ppt/slides/_rels/slide12.xml.rels ppt/slides/_rels/slide13.xml.rels ppt/slides/_rels/slide14.xml.rels ppt/slides/_rels/slide15.xml.rels ppt/slides/_rels/slide16.xml.rels ppt/slides/_rels/slide2.xml.rels ppt/slides/_rels/slide3.xml.rels ppt/slides/_rels/slide4.xml.rels ppt/slides/_rels/slide5.xml.rels ppt/slides/_rels/slide6.xml.rels ppt/slides/_rels/slide7.xml.rels ppt/slides/_rels/slide8.xml.rels ppt/slides/_rels/slide9.xml.rels [content_types].xml ekonometrik modellar parametrlarini baholashda eng kichik kvadratlar usulining metodologik ahamiyati reja: 1.eng kichik kvadratlar usuliga kirish 2.eng kichik kvadratlar usulining matematik asoslari 3.parametrlarni baholashda r-kvadrat statistikasi: model mosligini aniqlash 4.eng kichik kvadratlar usulining istiqbollari va rivojlanish yo'nalishlari eng kichik kvadratlar usuliga kirish asosiy maqsad eng kichik kvadratlar usulining asosiy maqsadi — kuzatilgan ma'lumotlar to'plamiga eng optimal tarzda mos keladigan chiziqli yoki chiziqli bo'lmagan modelni aniqlashdir. ushbu usul iqtisodiy jarayonlar va hodisalarni matematik jihatdan modellashtirish hamda ularning o'zaro bog'liqliklarini miqdoriy jihatdan baholash imkonini beradi. eng kichik kvadratlar prinsipi model chizig'i va har bir kuzatuv nuqtasi orasidagi vertikal masofalarning kvadratlari yig'indisini minimallashtirish orqali modelning eng samarali parametrlarini aniqlash, bu esa eng yaxshi moslikni ta'minlaydi. matematik asoslar parametrlarni hisoblash jarayoni statistik dispersiy

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a va kovariatsiya tushunchalariga tayanadi. ushbu yondashuv modelning o'zgaruvchilar orasidagi o'zaro bog'liqlikni aniq va miqdoriy jihatdan ifodalashga imkon beradi. oddiy chiziqli modelning asoslari va uning formulasi 1 model strukturasi ushbu modelda y bog'liq o'zgaruvchini, x esa mustaqil o'zgaruvchini ifodalaydi. ε tasodifiy xatolik (yoki xatolik haddi) bo'lib, modelda hisobga olinmagan barcha omillar ta'sirini aks ettiradi. 2 parametrlarning talqini β₀ — kesishma nuqtasi (intercept): model chizig'ining y-o'qini kesib o'tish nuqtasini anglatadi. boshqacha aytganda, mustaqil o'zgaruvchi x nolga teng bo'lgan holatda bog'liq o'zgaruvchi y ning kutilayotgan qiymatini bildiradi. β₁ — chiziqning qiyaligi (regressiya koeffitsienti): mustaqil o'zgaruvchi x bir birlikka o'zgarganda, bog'liq o'zgaruvchi y ning kutilayotgan o'zgarish miqdorini ko'rsatuvchi muhim koeffitsient. ε — tasodifiy xatolik (error term): nazariy modelda hisobga olinmagan va tasodifiy xarakterga ega bo'lgan barcha tashqi omillarning bog'liq o'zgaruvchiga ta'sirini aks ettiradi. bizning asosiy vazifamiz — eng kichik kvadratlar usuli (ekku) yordamida β₀ va β₁ parametrlarning eng optimal qiymatlarini aniqlash hamda ularning …

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a "residual" (qoldiq) deb ataladi. grafikda bu residuallar vizual tarzda ko'rsatilgan bo'lib, aynan shu masofalarning kvadratlari yig'indisi minimallashtiriladi, bu esa eng optimal mos keladigan chiziqni topish imkonini beradi. parametrlarni baholashda r-kvadrat statistikasi: model mosligini aniqlash 80% modelning tushuntirish qobiliyati agar r² = 0.8 bo'lsa, bu modelning ma'lumotlardagi umumiy o'zgaruvchanlikning 80% ini tushuntira olishini anglatadi. 100% mukammal moslik r² = 1 qiymati mukammal moslikni ifodalaydi, ya'ni barcha kuzatilgan ma'lumot nuqtalari regressiya chizig'ida joylashgan. 0% tushuntirish qobiliyatining yo'qligi r² = 0 bo'lganda, model ma'lumotlardagi o'zgaruvchanlikni tushuntirishda hech qanday samara bermaydi. r² ko'rsatkichi regressiya modelining sifatini baholashda muhim ahamiyatga ega bo'lgan asosiy statistik mezon hisoblanadi. iqtisodiy tadqiqotlarda, odatda, 0.7 dan yuqori bo'lgan r² qiymatlari modelning yetarli darajada ishonchli va ahamiyatli ekanligidan dalolat beradi. ishlab chiqarish hajmi va xarajatlar: amaliy tahlil ishlab chiqarish hajmi (ming birlik) xarajatlar (ming so'm) 50 655 75 913 100 1,172 125 1,431 150 1,689 regressiya tenglamasi xarajatlar = 138,533 …

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ekonometrik modellar parametrlarini baholash

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