This e-book is the product of Project Euclid and its mission to advance scholarly communication in the field of theoretical and applied mathematics and statistics. Project Euclid was developed and deployed by the Cornell University Library and is jointly managed by Cornell and the Duke University Press.

One of the more characteristic features of contemporary sociology is an increasing interest in theories. More and more theories are being developed in various areas of social investigation; we observe also an increasing number of verificational studies aimed primarily toward the verification of various theories. The essays presented in this volume deal with theories too, but they approach this problem from a methodological perspective. There fore it seems worthwhile in the preface to this volume to make a kind of general declaration about the author's aims and his approach to the subject of his interest, and about his view of the role of methodological reflection in the development of sciences. First let me say what methodology cannot do. It cannot be a substitute for the formulation of substantive theories, nor can it substitute for the empirical studies which confirm or reject such theories. Therefore its impact upon the development of any science, including the social sciences, is only indirect, by its undertaking the analysis of research tools and rules of scientific procedures. It can also propose certain standards for scientific procedures, but the application of these standards is the domain of substan tive researchers, and it is the substantive researchers who ultimately develop any science. Nevertheless the potential impact-of methodological reflection, even if only indirect, should not be underestimated.

Personal subjective opinions are one of the most important assets in management. Prediction markets are mechanisms that can be deployed to elicit and aggregate a group of people's opinions regarding the outcome of future events at any point in time. Prediction markets are exchange-traded markets where security values are tied to the outcome of future events. Prediction markets are systematically designed in a way that their market prices capture the crowd's consensus about the probability of a future event. Corporations harness internal prediction markets for managerial decision making and business forecasting. Prediction markets are traditionally designed for large and diverse populations, two properties that are not often displayed in corporate settings. Therefore special considerations must be given to prediction markets used in corporations. Our first contribution in this thesis is in addressing the issue of diversity, in the sense of risk preferences, in corporate prediction markets. We study prediction markets in the presence of risk averse or risk seeking agents that have unknown risk preferences. We show that such agents' behavior is not desirable for the purpose of information aggregation. We then characterize the agents' behavior with respect to prediction market parameters and offer a systematic method to market organizers that fine tunes market parameters so at to best mitigate the impact of a pool agents' risk-preferences. Our Second contribution in this thesis is in recommending prediction market mechanisms in different settings. There are many prediction market mechanisms with various advantages and weaknesses. The choice of a market mechanism can heavily affect the market accuracy and in turn, the success of a managerial decision, or a forecast based on prediction markets' prices. Using trade data from two real-world prediction markets, we study the two main types of prediction markets mechanism and provide the much-needed insight as to what market mechanism to choose in various situations.

Based upon ten case studies, Prediction explores how science-based predictions guide policy making and what this means in terms of global warming, biogenetically modifying organisms and polluting the environment with chemicals.

This book presents a unified treatment of the prediction process approach to continuous time stochastic processes. The underling idea is that there are two kinds of time: stationary physical time and the moving observer's time. By developing this theme, the author develops a theory of stochastic processes whereby two processes are considered which coexist on the same probability space. In this way, the observer' process is strongly Markovian. Consequently, any measurable stochastic process of a real parameter may be regarded as a homogeneous strong Markov process in an appropriate setting. This leads to a unifying principle for the representation of general processes in terms of martingales which facilitates the prediction of their properties. While the ideas are advanced, the methods are reasonable elementary and should be accessible to readers with basic knowledge of measure theory, functional analysis, stochastic integration, and probability on the level of the convergence theorem for positive super-martingales.

Despite developments in research and practice on using examinee response process data in assessment design, the use of such data in test validation is rare. Validation of Score Meaning in the Next Generation of Assessments Using Response Processes highlights the importance of validity evidence based on response processes and provides guidance to measurement researchers and practitioners in creating and using such evidence as a regular part of the assessment validation process. Response processes refer to approaches and behaviors of examinees when they interpret assessment situations and formulate and generate solutions as revealed through verbalizations, eye movements, response times, or computer clicks. Such response process data can provide information about the extent to which items and tasks engage examinees in the intended ways. With contributions from the top researchers in the field of assessment, this volume includes chapters that focus on methodological issues and on applications across multiple contexts of assessment interpretation and use. In Part I of this book, contributors discuss the framing of validity as an evidence-based argument for the interpretation of the meaning of test scores, the specifics of different methods of response process data collection and analysis, and the use of response process data relative to issues of validation as highlighted in the joint standards on testing. In Part II, chapter authors offer examples that illustrate the use of response process data in assessment validation. These cases are provided specifically to address issues related to the analysis and interpretation of performance on assessments of complex cognition, assessments designed to inform classroom learning and instruction, and assessments intended for students with varying cultural and linguistic backgrounds. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

The four-volume set LNAI 6881-LNAI 6884 constitutes the refereed proceedings of the 15th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2011, held in Kaiserslautern, Germany, in September 2011. Part 2: The total of 244 high-quality papers presented were carefully reviewed and selected from numerous submissions. The 70 papers of Part 2 are organized in topical sections on web intelligence, text and multimedia mining and retrieval, intelligent tutoring systems and e-learning environments, other / misc. intelligent systems topics, methods and techniques of artificial and computational intelligence in economics, finance and decision making, workshop on seamless integration of semantic technologies in computer-supported office work (sistcow), innovations in chance discovery, advanced knowledge-based systems, recent trends in knowledge engineering, smart systems, and their applications.

This monograph analyzes Nicholas Rescher’s system of pragmatic idealism. It also looks at his approach to prediction in science. Coverage highlights a prominent contribution to a central topic in the philosophy and methodology of science. The author offers a full characterization of Rescher’s system of philosophy. She presents readers with a comprehensive philosophico-methodological analysis of this important work. Her research takes into account different thematic realms: semantic, logical, epistemological, methodological, ontological, axiological, and ethical. The book features three, thematic-parts: I) General Coordinates, Semantic Features and Logical Components of Scientific Prediction; II) Predictive Knowledge and Predictive Processes in Rescher’s Methodological Pragmatism; and III) From Reality to Values: Ontological Features, Axiological Elements, and Ethical Aspects of Scientific Prediction. This insightful analysis offers a critical reconstruction of Rescher’s philosophy. The system he created is often characterized as pragmatic idealism that is open to some realist elements. He is a prominent representative of contemporary pragmatism who has made a great deal of contributions to the study of this topic. This area is crucial for science and it has been little considered in the philosophy of science.