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"Gini's mean difference (GMD) was first introduced by Corrado Gini in 1912 as an alternative measure of variability. GMD and the parameters which are derived from it (such as the Gini coefficient or the concentration ratio) have been in use in the area of income distribution for almost a century. In practice, the use of GMD as a measure of variability is justified whenever the investigator is not ready to impose, without questioning, the convenient world of normality. This makes the GMD of critical importance in the complex research of statisticians, economists, econometricians, and policy makers. This book focuses on imitating analyses that are based on variance by replacing variance with the GMD and its variants. In this way, the text showcases how almost everything that can be done with the variance as a measure of variability, can be replicated by using Gini. Beyond this, there are marked benefits to utilizing Gini as opposed to other methods. One of the advantages of using Gini methodology is that it provides a unified system that enables the user to learn about various aspects of the underlying distribution. It also provides a systematic method and a unified terminology. Using Gini methodology can reduce the risk of imposing assumptions that are not supported by the data on the model. With these benefits in mind the text uses the covariance-based approach, though applications to other approaches are mentioned as well."--Publisher's description

This book, an outgrowth of the 10th International Symposium on Dynamic Games, presents current developments of the theory of dynamic games and its applications. The text uses dynamic game models to approach and solve problems pertaining to pursuit-evasion, marketing, finance, climate and environmental economics, resource exploitation, as well as auditing and tax evasions. It includes chapters on cooperative games, which are increasingly drawing dynamic approaches to their classical solutions.

Illegal sharing of cultural goods on the Internet has become a massive reality in today's connected society. Numerous studies have been performed to try and evaluate the impact of these practices on the industry of cultural goods, and how much harm, if any, they have entailed. The effect of legal and technical responses to limit pirating has also been investigated, showing in general inconclu-sive effect. Instead of penalizing illegal actors -providers and/or consumers -, a totally different approach has been proposed recently by the french government agency Hadopi. The idea is to offer the possibility to sites that illegally share cultural goods to become legal in exchange of a retribution proportional to their activity. The present work builds on parts of the elegant model proposed in [1] to study the economic feasibility of such a scheme under various assumptions on the behaviour of the different actors involved. Our main finding is that, supposing that more popular goods are more prone to pirating, a retribution of the order of the increase in benefit per user gained by legal-ized sites does indeed lead to a win-win situation for both producers/sellers of cultural goods and willing-to-be-legalized sites.

Illegal sharing of cultural goods on the Internet has become a massive reality in today's connected society. Numerous studies have been performed to try and evaluate the impact of these practices on the industry of cultural goods, and how much harm, if any, they have entailed. The effect of legal and technical responses to limit pirating has also been investigated, showing in general inconclu-sive effect. Instead of penalizing illegal actors -providers and/or consumers -, a totally different approach has been proposed recently by the french government agency Hadopi. The idea is to offer the possibility to sites that illegally share cultural goods to become legal in exchange of a retribution proportional to their activity. The present work builds on parts of the elegant model proposed in [1] to study the economic feasibility of such a scheme under various assumptions on the behaviour of the different actors involved. Our main finding is that, supposing that more popular goods are more prone to pirating, a retribution of the order of the increase in benefit per user gained by legal-ized sites does indeed lead to a win-win situation for both producers/sellers of cultural goods and willing-to-be-legalized sites.

Illegal sharing of cultural goods on the Internet has become a massive reality in today's connected society. Numerous studies have been performed to try and evaluate the impact of these practices on the industry of cultural goods, and how much harm, if any, they have entailed. The effect of legal and technical responses to limit pirating has also been investigated, showing in general inconclu-sive effect. Instead of penalizing illegal actors -providers and/or consumers -, a totally different approach has been proposed recently by the french government agency Hadopi. The idea is to offer the possibility to sites that illegally share cultural goods to become legal in exchange of a retribution proportional to their activity. The present work builds on parts of the elegant model proposed in [1] to study the economic feasibility of such a scheme under various assumptions on the behaviour of the different actors involved. Our main finding is that, supposing that more popular goods are more prone to pirating, a retribution of the order of the increase in benefit per user gained by legal-ized sites does indeed lead to a win-win situation for both producers/sellers of cultural goods and willing-to-be-legalized sites.

AbstractAyache presents a view of markets and mathematics that attempts to conform to the philosophies of Alain Badiou and Quentin Meillassoux. However, this attempt is unsuccessful because Ayache adopts a view of probability rooted in nineteenth-century conceptions that cannot accommodate the radical uncertainty of the markets. This is unfortunate as it is reasonable to believe that the ideas of Badiou and Meillassoux, when synthesised with contemporary ideas of probability, could offer interesting insights. Roffe presents a better argued synthesis of Deleuze and markets, however he makes similar assumptions about contemporary probability that undermine his conclusions.

"Many important applications in global optimization, algebra, probability and statistics, applied mathematics, control theory, financial mathematics, inverse problems, etc. can be modeled as a particular instance of the Generalized Moment Problem (GMP). This book introduces a new general methodology to solve the GMP when its data are polynomials and basic semi-algebraic sets. This methodology combines semidefinite programming with recent results from real algebraic geometry to provide a hierarchy of semidefinite relaxations converging to the desired optimal value. Applied on appropriate cones, standard duality in convex optimization nicely expresses the duality between moments and positive polynomials. In the second part, the methodology is particularized and described in detail for various applications, including global optimization, probability, optimal control, mathematical finance, multivariate integration, etc., and examples are provided for each particular application." -- Book cover

The goal of Disaster Risk Management (DRM) is to ensure that society continues to function, thrive, and recover quickly despite shocks arising from natural or human actions; to ensure, in short, that natural hazards do not become disasters. Success in the world of DRM means 'nothing happens,' but this poses a dilemma towards recognising and incentivising successful DRM interventions since they are made invisible by the very nature of their success. How then do we highlight and learn from successes if we do not see them? Likewise, how do we incentivise policymakers to make better risk-informed decisions when they are not credited for pro-active actions nor accountable for the consequences of doing nothing? This study discusses four types of situations where successful DRM interventions are made invisible: (i) success made invisible in the midst of broader disaster, (ii) success made invisible by nature of the success, (iii) success made invisible due to yet unrealised benefits, (iv) success made invisible due to the randomness of the specific outcome. We propose the use of probabilistic counterfactual analysis to calculate and highlight the `probabilistic lives saved' from disaster risk management interventions, that would otherwise remain unnoticed. Two case-studies are provided, a school seismic retrofit program in Nepal and a cyclone evacuation effort in India. An important conclusion that emerges from these studies is that the value of risk reduction interventions should not be judged on the basis of specific outcomes, but on the basis of a broader exploration of potential outcomes. The shift in focus from realised outcome to counterfactual alternative provides a framework to identify and learn from successes in DRM, and reward individuals and institutions who have displayed political bravery in committing to the implementation of DRM measures despite invisible benefits. ; Ministry of Education (MOE) ; National Research Foundation (NRF) ; Published version ; We thank Dr. Nama Budhathoki, Kathmandu Living Labs ...

"Ostrowski inequality is one of the celebrated inequalities in Mathematics.
The main purpose of our study is to generalize the result of Ostrowski-Gruss
type inequality for first differentiable mappings and apply it to probability density
functions, composite quadrature rules and special means."

Book reviewed in this article:Introduction to Probability and Mathematical Statistics, Z. W. BirnbaumThe Paper Industry and European Integration, R. BolaffiMethods of least squares and principles of the theory of observations, Yu. V. LinnikFundamentals of Scientific Mathematics, George E. OwenDecomposition of Superpositions of Distribution Functions, P. MedgyessyMathematical Methods and Theory in Games, Programming and Economics, S. K. arlinStatistical Analysis and Optimization of Systems, E. L. PetersonStudies in applied probability and management science, edited by Kenneth J. Arrow, Samuel Karlin and Herbert Scarf

Statistics are used throughout businesses to present and analyse data and decide on best practice. Simplified Business Statistics Using SPSS provides a practical approach to these concepts and their applications in business, economics and other areas of data analytics. This book guides the reader though these concepts without assuming prior knowledge and is an ideal reference for business analytics students and researchers in related fields. Features Includes simplified statistical contents and a step-by-step guide on how to apply statistical concepts by perform analysis using Statistical Package for Social Sciences together with an interpretation of the statistical analysis output Provides a wide range of data sets to be used for examples and illustrations Designed to be accessible to readers with varied backgrounds

"This book is an overview of how practitioners can work with data from the US Census Bureau using the R programming language. The book will focus on data acquisition and wrangling as well as data analysis and modeling of aggregate and individual-level decennial Census and American Community Survey data. It is designed to be useful for both beginners and advanced users of both R and Census data. Additionally, the book will take advantage of cutting-edge developments in both data wrangling and spatial data analysis in R"--

"This book provides an introduction to the use of statistical concepts and methods to model and analyze financial data. The ten chapters of the book fall naturally into three sections. Chapters 1 to 3 cover some basic concepts of finance, focusing on the properties of returns on an asset. Chapters 4 through 6 cover aspects of portfolio theory and the methods of estimation needed to implement that theory. The remainder of the book, Chapters 7 through 10, discusses several models for financial data, along with the implications of those models for portfolio theory and for understanding the properties of return data. The audience for the book is students majoring in Statistics and Economics as well as in quantitative fields such as Mathematics and Engineering. Readers are assumed to have some background in statistical methods along with courses in multivariate calculus and linear algebra."--Provided by publisher.

This guide is for practicing statisticians and data scientists who use IBM SPSS for statistical analysis of big data in business and finance. This is the first of a two-part guide to SPSS for Windows, introducing data entry into SPSS, along with elementary statistical and graphical methods for summarizing and presenting data. Part I also covers the rudiments of hypothesis testing and business forecasting while Part II will present multivariate statistical methods, more advanced forecasting methods, and multivariate methods. IBM SPSS Statistics offers a powerful set of statistical and information analysis systems that run on a wide variety of personal computers. The software is built around routines that have been developed, tested, and widely used for more than 20 years. As such, IBM SPSS Statistics is extensively used in industry, commerce, banking, local and national governments, and education. Just a small subset of users of the package include the major clearing banks, the BBC, British Gas, British Airways, British Telecom, the Consumer Association, Eurotunnel, GSK, TfL, the NHS, Shell, Unilever, and W.H.S. Although the emphasis in this guide is on applications of IBM SPSS Statistics, there is a need for users to be aware of the statistical assumptions and rationales underpinning correct and meaningful application of the techniques available in the package; therefore, such assumptions are discussed, and methods of assessing their validity are described. Also presented is the logic underlying the computation of the more commonly used test statistics in the area of hypothesis testing. Mathematical background is kept to a minimum. Abdulkader Aljandali, Ph. D., is a Senior Lecturer in Quantitative Finance and Business Forecasting at Regent's University London. He acts as a visiting professor at overseas institutions in Canada, France, and Morocco.