Two Statistical Models on European and Croatian Information Society

The Council of the European Union (EU) defined information society (IS) with new Strategy i2010 for information and communication technology (ICT). Eurostat has European statistics for EU countries. Central bureau of statistics of Croatia and IDC Adriatics have numerical data benchmark indicators for information society for Croatia as candidate country. In our paper we use eight numerical data variables in two statistical models. Factor analysis model looks for the most important variables for information society. Causal structure model defines causal relation between these variables for development of information society in EU and Croatia

Forecasting Model of Road Traffic Accidents in Urban Areas

Cestovne prometne nesreće, a posebice teži oblici (sa smrtnim posljedicama i težim ozljedama) na nacionalnom i međunarodnom planu predstavljaju ozbiljan socioekonomski i politički problem. Jedan od pristupa rješavanju toga problema jest razvoj pouzdanih prognostičkih modela CPN-a koji se temelje na atributima koji utječu na nesreće. Njihovom primjenom i kvantifikacijom ostvaruju se saznanja o čimbenicima sigurnosti i posljedicama različitih kategorija CPN-a. Pritom stručnjaci dobivaju pouzdan alat za sustavnu procjenu stanja sigurnosti. S obzirom na velik broj ulaznih parametara, literatura o prometnim nesrećama još uvijek ne pruža univerzalno prihvaćen te znanstveno utemeljen pristup izradi takvih procesa. Prepoznajući važnost statističkih metoda za povezivanje, klasifikaciju te predviđanje stopa kretanja CPN-a, kao i činjenicu da takva istraživanja nisu provedena na prostoru nacionalnoga cestovnog prometnog sustava, cilj je ovoga znanstvenog istraživanja izrada vjerodostojnoga prognostičkog modela CPN-a za urbana gradska područja, odnosno uspostavljanje uzročno-posljedične veze između prometnih nesreća i relevantnih uzroka njihovih nastanka, ljudske i cestovno-prometne varijable. Predloženi model CPN-a u daljnjim istraživanjima služit će kao podloga za izradu detaljnije analize utvrđivanja i rangiranja glavnih uzročnika nastanka prometnih nesreća te korelaciju u pogledu vrsta i posljedica cestovnih nesreća. Osnovnu podlogu na temelju koje su provedena daljnja istraživanja i analize čine statistička izvješća svih registriranih cestovnih prometnih nesreća na području Grada Zagreba i Zagrebačke županije u periodu od 10 godina: od 2004. do 2013. godine, uz interpretaciju tradicionalnih statističkih metoda primjenjivih na obrađenim ulaznim podatcima. Rezultati analize, kao i izrada kauzalnoga prognostičkog modela omogućit će povećanje razine sigurnosti i kontrolu odvijanja cestovnoga prometnog sustava u kontekstu određivanja ciljanih represivnih i preventivnih mjera kako bi se stope CPN-a u urbanim gradskim područjima umanjile te kako bi se anuliralo njihove negativne posljedice te omogućilo sigurnije planiranje gradskih prometnih sustava.Road traffic accidents, particularly in their severe forms (with fatal consequences and serious injuries) represent a serious socio-economic and political problem on both national and international level. One approach for solving this problem is the development of reliable forecasting models of RTA which are based on attributes that affect accidents. By means of their application and quantification, it is possible to obtain cognizance relating to safety factors and consequences of various categories of RTA's. In doing so, experts receive a reliable tool for systematic assessment of the security situation. Given the large number of input parameters, the literature on traffic accidents still does not provide a universally accepted and scientifically based approach to development of such processes. Recognizing the importance of statistical methods for connecting, classification and RTA's prediction rate movements, and the fact that such studies have not been conducted in the area of national road transport system, the goal of this scientific research is to develop a credible prediction model of RTA for urban metropolitan areas and to establish cause and effect link between accidents and relevant causes of their origin, human and road-traffic variable. In further research, the proposed RTA model will serve as the basis for making a more detailed analysis of determining and ranking the main causes of accidents and correlation in terms of type and consequences of road accidents. The foundation of research and analysis are statistical reports of all registered road accidents in the City of Zagreb and Zagreb County for the period of 10 years, from 2004 to 2013, with interpretation of traditional statistical methods applicable to the processed input data. Results of the analysis and development of causal forecasting model will increase the level of security and control of a road transport system in the context of determining targeted repressive and preventive measures, in order to reduce RTA rates in urban metropolitan areas and annul their negative consequences, as well as to enable more secure planning of urban transport systems

Forecasting Model of Road Traffic Accidents in Urban Areas

Cestovne prometne nesreće, a posebice teži oblici (sa smrtnim posljedicama i težim ozljedama) na nacionalnom i međunarodnom planu predstavljaju ozbiljan socioekonomski i politički problem. Jedan od pristupa rješavanju toga problema jest razvoj pouzdanih prognostičkih modela CPN-a koji se temelje na atributima koji utječu na nesreće. Njihovom primjenom i kvantifikacijom ostvaruju se saznanja o čimbenicima sigurnosti i posljedicama različitih kategorija CPN-a. Pritom stručnjaci dobivaju pouzdan alat za sustavnu procjenu stanja sigurnosti. S obzirom na velik broj ulaznih parametara, literatura o prometnim nesrećama još uvijek ne pruža univerzalno prihvaćen te znanstveno utemeljen pristup izradi takvih procesa. Prepoznajući važnost statističkih metoda za povezivanje, klasifikaciju te predviđanje stopa kretanja CPN-a, kao i činjenicu da takva istraživanja nisu provedena na prostoru nacionalnoga cestovnog prometnog sustava, cilj je ovoga znanstvenog istraživanja izrada vjerodostojnoga prognostičkog modela CPN-a za urbana gradska područja, odnosno uspostavljanje uzročno-posljedične veze između prometnih nesreća i relevantnih uzroka njihovih nastanka, ljudske i cestovno-prometne varijable. Predloženi model CPN-a u daljnjim istraživanjima služit će kao podloga za izradu detaljnije analize utvrđivanja i rangiranja glavnih uzročnika nastanka prometnih nesreća te korelaciju u pogledu vrsta i posljedica cestovnih nesreća. Osnovnu podlogu na temelju koje su provedena daljnja istraživanja i analize čine statistička izvješća svih registriranih cestovnih prometnih nesreća na području Grada Zagreba i Zagrebačke županije u periodu od 10 godina: od 2004. do 2013. godine, uz interpretaciju tradicionalnih statističkih metoda primjenjivih na obrađenim ulaznim podatcima. Rezultati analize, kao i izrada kauzalnoga prognostičkog modela omogućit će povećanje razine sigurnosti i kontrolu odvijanja cestovnoga prometnog sustava u kontekstu određivanja ciljanih represivnih i preventivnih mjera kako bi se stope CPN-a u urbanim gradskim područjima umanjile te kako bi se anuliralo njihove negativne posljedice te omogućilo sigurnije planiranje gradskih prometnih sustava.Road traffic accidents, particularly in their severe forms (with fatal consequences and serious injuries) represent a serious socio-economic and political problem on both national and international level. One approach for solving this problem is the development of reliable forecasting models of RTA which are based on attributes that affect accidents. By means of their application and quantification, it is possible to obtain cognizance relating to safety factors and consequences of various categories of RTA's. In doing so, experts receive a reliable tool for systematic assessment of the security situation. Given the large number of input parameters, the literature on traffic accidents still does not provide a universally accepted and scientifically based approach to development of such processes. Recognizing the importance of statistical methods for connecting, classification and RTA's prediction rate movements, and the fact that such studies have not been conducted in the area of national road transport system, the goal of this scientific research is to develop a credible prediction model of RTA for urban metropolitan areas and to establish cause and effect link between accidents and relevant causes of their origin, human and road-traffic variable. In further research, the proposed RTA model will serve as the basis for making a more detailed analysis of determining and ranking the main causes of accidents and correlation in terms of type and consequences of road accidents. The foundation of research and analysis are statistical reports of all registered road accidents in the City of Zagreb and Zagreb County for the period of 10 years, from 2004 to 2013, with interpretation of traditional statistical methods applicable to the processed input data. Results of the analysis and development of causal forecasting model will increase the level of security and control of a road transport system in the context of determining targeted repressive and preventive measures, in order to reduce RTA rates in urban metropolitan areas and annul their negative consequences, as well as to enable more secure planning of urban transport systems

Causal Bayes Model of Mathematical Competence in Kindergarten

In this paper authors define mathematical competences in the kindergarten. The basic objective was to measure the mathematical competences or mathematical knowledge, skills and abilities in mathematical education. Mathematical competences were grouped in the following areas: Arithmetic and Geometry. Statistical set consisted of 59 children, 65 to 85 months of age, from the Kindergarten Milan Sachs from Zagreb. The authors describe 13 variables for measuring mathematical competences. Five measuring variables were described for the geometry, and eight measuring variables for the arithmetic. Measuring variables are tasks which children solved with the evaluated results. By measuring mathematical competences the authors make causal Bayes model using free software Tetrad 5.2.1-3. Software makes many causal Bayes models and authors as experts chose the model of the mathematical competences in the kindergarten. Causal Bayes model describes five levels for mathematical competences. At the end of the modeling authors use Bayes estimator. In the results, authors describe by causal Bayes model of mathematical competences, causal effect mathematical competences or how intervention on some competences cause other competences. Authors measure mathematical competences with their expectation as random variables. When expectation of competences was greater, competences improved. Mathematical competences can be improved with intervention on causal competences. Levels of mathematical competences and the result of intervention on mathematical competences can help mathematical teachers

Policy and Programs for Cycling in the City of Zagreb – A Critical Review

Studying cycling traffic issues in a beginner city – City of Zagreb, stems from unclear development policy, an increase in cycling volume, a large number of traffic accidents, an inadequate infrastructure and legislation, a small number of high quality studies and published papers, and the question, did current cycling policy and programs advance cycling? A comprehensive search of available literature, including data from the Zagreb Traffic Department, was made. These data do not adequately address the direction of causality, such as whether current cycling policy and programs advance cycling or whether cycling demand led to increased levels of cycling. This review paper suggests that, it is not yet possible to evaluate which pro-bicycle packages are the most effective and, development of cycling traffic requires a coordinated holistic planning strategy. Results could serve as a beacon light for similarly sized beginner cities, especially those who are located in South-eastern and Eastern Europe