20.500.12556/DKUM-14276 REGRESIJSKA ANALIZA REGRESSION ANALYSIS V diplomskem delu je predstavljena regresijska analiza s poudarkom na linearni regresiji in večkratni regresiji. Na začetku sta v poglavju osnovni pojmi opisani korelacijska analiza in analiza variance, ki sta pomembni za razumevanje diplomskega dela. V nadaljevanju je predstavljen regresijski model. Nato sta v osrednjem delu predstavljeni dve poglavji: linearna regresija in večkratna regresija. V prvem je opisana metoda najmanjših kvadratov, ki je pomembna za pridobivanje ocen regresijskih parametrov. Predstavljen je tudi model in preverjanje podatkov, ter osnovni statistični podatki (standardna napaka modela, tabela analize variance, determinacijski koeficient, statistiki F in T, ki sta pomembni za testiranje ničelnih hipotez). V drugem je predstavljen postopek, kako priti do ocen parametrov, ter model in preverjanje podatkov. Obe poglavji sta podprti z zgledi, za katere je bil pri obdelavi podatkov uporabljen statistični program SPSS. V nadaljevanju so opisani praktični premisleki v regresijski analizi z izbiro regresijske enačbe, eksperimentalnimi cilji in selektivno metodo. Nato je predstavljena še uporaba regresijske analize, ki temelji na obliki regresijske enačbe ter na ocenjevanju in napovedovanju. Na koncu je z zgledoma predstavljena še nelinearna regresija. The graduation thesis presents regression analysis with emphasis on linear regression and multiple regression. The first chapter describes basic concepts of the correlation analysis and analysis of variance, which are important for understanding the thesis. Further, a regression model is presented. The central part of the thesis consists of two chapters: linear regression and multiple regression. The first one describes the method of least squares, which is important for obtaining estimates of regression parameters. A model is presented including a verification of data and basic statistics (standard error of the model, table analysis of variance, coefficient of determination, F and T statistics, which are important for testing the null hypothesis). In the second one we describe a method for obtaining estimates of parameters, and design and verification of data. In both sections many examples are given, which were obtained using statistical data processing program SPSS. Next, some practical arguments in regression analysis are described including the choice of regression equation, the experimental objectives and selective method. We also present applications of regression analysis based on a form of regression equation, and also on evaluation and prediction. Finally, we give two examples presenting nonlinear regression. linearna regresija večkratna regresija nelinearna regresija analiza variance linear regression multiple regression nonlinear regression analysis of variance true true false [A. Korenjak] Slovenski jezik Angleški jezik Diplomsko delo 2010-06-03 17:21:43 2010-07-08 15:38:27 2022-04-12 21:53:58 2023-12-17 03:24:51 2010 0 Maribor 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 51(043.2) 17742344 URN:SI:UM:DK:H97ROC4W UNI_Korenjak_Andreja_2010.pdf UNI_Korenjak_Andreja_2010.pdf 1 894F4D67AA034132E9EDE20BCC2A43AC 684b41dd82b1b0f12f6f81df7d3d8d49cb7567493dc1b930bc6f7a1d0c061cb7 1dddd3cc-7c04-11eb-bb7a-00155d0001ca 20.500.12556/dkum/357b6915-b410-433c-b2cb-c986e7d683f3 https://dk.um.si/Dokument.php?lang=slv&id=15101 Fakulteta za naravoslovje in matematiko 0 0 0