Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus background. The first part of the book provides a broad view of probability including foundations, conditional probability, discrete and continuous distributions, and joint distributions. Statistical inference is presented completely from a Bayesian perspective. The text introduces inference and prediction for a single proportion and a single mean from Normal sampling. After fundamentals of Markov Chain Monte Carlo algorithms are introduced, Bayesian inference is described for hierarchical and regression models including logistic regression. The book presents several case studies motivated by some historical Bayesian studies and the authors’ research. This text reflects modern Bayesian statistical practice. Simulation is introduced in all the probability chapters and extensively used in the Bayesian material to simulate from the posterior and predictive distributions. One chapter describes the basic tenets of Metropolis and Gibbs sampling algorithms; however several chapters introduce the fundamentals of Bayesian inference for conjugate priors to deepen understanding. Strategies for constructing prior distributions are described in situations when one has substantial prior information and for cases where one has weak prior knowledge. One chapter introduces hierarchical Bayesian modeling as a practical way of combining data from different groups. There is an extensive discussion of Bayesian regression models including the construction of informative priors, inference about functions of the parameters of interest, prediction, and model selection. The text uses JAGS (Just Another Gibbs Sampler) as a general-purpose computational method for simulating from posterior distributions for a variety of Bayesian models. An R package ProbBayes is available containing all of the book datasets and special functions for illustrating concepts from the book. A complete solutions manual is available for instructors who adopt the book in the Additional Resources section.
China's recent economic transformation and integration into the world economy has coincided with increasing pressure for corporate law reform to make corporate social responsibility (CSR) integral to business and management strategy in China. This timely book critically analyses contemporary notions of CSR in China, discussing theory and practice alongside legal responses in this emerging field. Jingchen Zhao uniquely combines the history, traditions and social policies of China with Chinese law, explaining the significance of path dependence in China. He presents an in-depth debate on the difficulties involved in transplanting developed legal principles directly into Chinese society, and takes a detailed look at the CSR provisions in Chinese company law which aimed to put social and environmental concerns onto the corporate agenda. He suggests how these laws could be more effectively and efficiently enforced with reference to UK law, and explores specific issues including: * Chinese Company Law 2006 * the 'Harmonious Society' in China * the 2008 Financial Crisis and its impact on the Chinese economy * recent corporate scandals including the Sanlu Baby Milk scandal, the Wenchuan earthquake and CSR donations, the Beijing Olympic Games and CSR, and the Fujia chemical plant. This book will prove an enlightening read for academics and practitioners in the fields of law, business and management interested in CSR and the law in contemporary China.
This book examines corporate governance rules in China, and highlights the deficiencies in current company law, with the purpose of arguing for a more effective derivative action mechanism, for the benefit of shareholders and their companies.
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