Migration has a principal influence on countries’ population changes. Thus, the issues connected with the causes, effects and directions of people’s movements are a common topic of political and academic discussions.
The aim of this paper is to analyse the spatial distribution of officially registered foreign migration in Poland in 2012. GIS tools are implemented for data visualization and statistical analysis. Geographically weighted regression (GWR) is used to estimate the impact of unemployment, wages and other socioeconomic variables on the foreign emigration and immigration measure. GWR provides spatially varying estimates of model parameters that can be presented on a map, giving a useful graphical representation of spatially varying relationships.
In the presence of massive data coming with high heterogeneity we need to change our statistical thinking and statistical education in order to adapt both - classical statistics and software developments that address new challenges. Significant developments include open data, big data, data visualisation, and they are changing the nature of the evidence that is available, the ways in which it is presented and the skills needed for its interpretation. The amount of information is not the most important issue – the real challenge is the combination of the amount and the complexity of data. Moreover, a need arises to know how uncertain situations should be dealt with and what decisions should be taken when information is insufficient (which can also be observed for large datasets). In the paper we discuss the idea of computational statistics as a new approach to statistical teaching and we try to answer a question: how we can best prepare the next generation of statisticians.
Most data mining projects in spatial economics start with an evaluation of a set of attribute variables on a sample of spatial entities, looking for the existence and strength of spatial autocorrelation, based on the Moran’s and the Geary’s coefficients, the adequacy of which is rarely challenged, despite the fact that when reporting on their properties, many users seem likely to make mistakes and to foster confusion. My paper begins by a critical appraisal of the classical definition and rational of these indices. I argue that while intuitively founded, they are plagued by an inconsistency in their conception. Then, I propose a principled small change leading to corrected spatial autocorrelation coefficients, which strongly simplifies their relationship, and opens the way to an augmented toolbox of statistical methods of dimension reduction and data visualization, also useful for modeling purposes. A second section presents a formal framework, adapted from recent work in statistical learning, which gives theoretical support to our definition of corrected spatial autocorrelation coefficients. More specifically, the multivariate data mining methods presented here, are easily implementable on the existing (free) software, yield methods useful to exploit the proposed corrections in spatial data analysis practice, and, from a mathematical point of view, whose asymptotic behavior, already studied in a series of papers by Belkin & Niyogi, suggests that they own qualities of robustness and a limited sensitivity to the Modifiable Areal Unit Problem (MAUP), valuable in exploratory spatial data analysis.
Marin Fotache, Gabriela Mesnita, Florin Dumitriu and Georgiana Olaru
Information Systems (IS) analysts and designers have been key members in software development teams. From waterfall to Rational Unified Process, from UML to agile development, IS modelers have faced many trends and buzzwords. Even if the topic of models and modeling tools in software development is important, there are no many detailed studies to identify for what the developers, customers and managers decide to use the modeling and specific tools. Despite the popularity of the subject, studies showing what tools the IS modelers prefer are scarce, and quasi-non-existent, when talking about Romanian market. As Romania is an important IT outsourcing market, this paper investigated what methods and tools Romanian IS analysts and designers apply. In this context, the starting question of our research focuses on the preference of the developers to choose between agile or non-agile methods in IT projects. As a result, the research questions targeted the main drivers in choosing specific methods and tools for IT projects deployed in Romanian companies. Also, one of the main objectives of this paper was to approach the relationship between the methodologies (agile or non-agile), diagrams and other tools (we refer in our study to the CASE features) with other variables/metrics of the system/software development project. The observational study was conducted based on a survey filled by IS modelers in Romanian IT companies. The data collected were processed and analyzed using Exploratory Data Analysis. The platform for data visualization and analysis was R.
Andrzej Cwynar, Wiktor Cwynar, Robert Pater and Piotr Kaźmierkiewicz
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Subject and purpose of work: The study attempts to examine the trade unfairness and transboundary bottlenecks between Bangladesh and India with a view to prosper a balanced trade and sustained water cooperation.
Materials and methods: The study is based on secondary data and statistical information. Mixed research methods such as qualitative, quantitative and data visualization techniques are adopted in this study to assess the political economy of river basin management, loss and damage assessment and trade situation assessment.
Results: Due to upstream intervention, the North-Western region of Bangladesh has lost 4254218 metric tons of rice production during 2006-2014 cropping years which value is $1036 million. During the same period, the trade deficit of Bangladesh stood at $5.58 billion with India due to the diverse tariff and non-tariff barriers which triggers tension between this close neighbor.
Conclusions: The trade and water co-operation should be extended among the South Asian countries including India and Bangladesh without delay to obtain the maximum benefit and economic prosperity.
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