Features the use of Bayesian statistics to gain insights from
empirical data
Featuring an accessible approach, "Bayesian Methods for
Management and Business: Pragmatic Solutions for Real Problems"
demonstrates how Bayesian statistics can help to provide insights
into important issues facing business and management. The book
draws on multidisciplinary applications and examples and utilizes
the freely available software WinBUGS and R to illustrate the
integration of Bayesian statistics within data-rich
environments.
Computational issues are discussed and integrated with coverage
of linear models, sensitivity analysis, Markov Chain Monte Carlo
(MCMC), and model comparison. In addition, more advanced models
including hierarchal models, generalized linear models, and latent
variable models are presented to further bridge the theory and
application in real-world usage.
"Bayesian Methods for Management and Business: Pragmatic
Solutions for Real Problems "alsofeatures: Numerous real-world
examples drawn from multiple management disciplines such as
strategy, international business, accounting, and information
systemsAn incremental skill-building presentation based on
analyzing data sets with widely-applicable models of increasing
complexityAn accessible treatment of Bayesian statistics that is
integrated with a broad range of business and management issues and
problemsA practical problem-solving approach to illustrate how
Bayesian statistics can help provide insight into important issues
facing business and managementThe use of WinBUGS and R to showcase
the benefits of Bayesian statistics for the increasingly data-rich
business environment
"Bayesian Methods for Management and Business: Pragmatic
Solutions for Real Problems" is an important textbook for Bayesian
statistics courses at the advanced MBA-level and also for business
and management PhD candidates as a first course in methodology. In
addition, the book is a useful resource for management scholars and
practitioners as well as business academics and practitioners who
need to broaden their methodological skill sets.
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