Northeastern Illinois University

About: Northeastern Illinois University is a education organization based out in Chicago, Illinois, United States. It is known for research contribution in the topics: Population & Politics. The organization has 838 authors who have published 1630 publications receiving 37078 citations. The organization is also known as: NEIU & Chicago Teachers College (North Side).

Learning Bayesian networks

Abstract: Preface. I. BASICS. 1. Introduction to Bayesian Networks. 2. More DAG/Probability Relationships. II. INFERENCE. 3. Inference: Discrete Variables. 4. More Inference Algorithms. 5. Influence Diagrams. III. LEARNING. 6. Parameter Learning: Binary Variables. 7. More Parameter Learning. 8. Bayesian Structure Learning. 9. Approximate Bayesian Structure Learning. 10. Constraint-Based Learning. 11. More Structure Learning. IV. APPICATIONS. 12. Applications. Bibliography. Index.

Autoethnography: An Overview

Abstract: Autoethnography is an approach to research and writing that seeks to describe and systematically analyze personal experience in order to understand cultural experience. This approach challenges canonical ways of doing research and representing others and treats research as a political, socially-just and socially-conscious act. A researcher uses tenets of autobiography and ethnography to do and write autoethnography. Thus, as a method, autoethnography is both process and product. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs1101108

Probabilistic Reasoning In Expert Systems: Theory and Algorithms

Abstract: This text is a reprint of the seminal 1989 book Probabilistic Reasoning in Expert systems: Theory and Algorithms, which helped serve to create the field we now call Bayesian networks. It introduces the properties of Bayesian networks (called causal networks in the text), discusses algorithms for doing inference in Bayesian networks, covers abductive inference, and provides an introduction to decision analysis. Furthermore, it compares rule-base experts systems to ones based on Bayesian networks, and it introduces the frequentist and Bayesian approaches to probability. Finally, it provides a critique of the maximum entropy formalism. Probabilistic Reasoning in Expert Systems was written from the perspective of a mathematician with the emphasis being on the development of theorems and algorithms. Every effort was made to make the material accessible. There are ample examples throughout the text. This text is important reading for anyone interested in both the fundamentals of Bayesian networks and in the history of how they came to be. It also provides an insightful comparison of the two most prominent approaches to probability.

Test Anxiety and Academic Performance in Undergraduate and Graduate Students.

Abstract: This study investigated the relationship between test anxiety and academic performance in 4,000 undergraduate and 1,414 graduate students and found a significant but small inverse relationship between test anxiety and grade point average (GPA) in both groups. Low-test-anxious undergraduates averaged a B+, whereas high-test-anxious students averaged a B. Low-test-anxious female graduate students had significantly higher GPAs than high-test-anxious female graduate students, but there were no significant GPA differences between low- and high-test-anxious male graduate students. Female undergraduates had significantly higher test anxiety and higher GPAs than male undergraduates, and female graduate students had significantly higher test anxiety and higher GPAs than male graduate students.

Organizational Absorptive Capacity and Responsiveness: An Empirical Investigation of Growth‐Oriented SMEs

Abstract: This study examines the relationship between firm absorptive capacity and organizational responsiveness in the context of growth–oriented small and medium–sized enterprises (SMEs). By testing the d...