Covering the technical and professional skills needed by analysts in the academic, private, and public sectors, this text systematically teaches novices how to apply algorithms to real data and how to recognize potential pitfalls. It concentrates on the interpretation, strengths, and weaknesses of analytical techniques, along with challenges encountered by analysts in their daily work. The author also shares various lessons learned from applying analytics in the real world. Example data sets used in the text are available for download online so that readers can test their own analytic routines.…mehr
Covering the technical and professional skills needed by analysts in the academic, private, and public sectors, this text systematically teaches novices how to apply algorithms to real data and how to recognize potential pitfalls. It concentrates on the interpretation, strengths, and weaknesses of analytical techniques, along with challenges encountered by analysts in their daily work. The author also shares various lessons learned from applying analytics in the real world. Example data sets used in the text are available for download online so that readers can test their own analytic routines.
Dr. Evan S. Levine is an analytics professional specializing in homeland security and counterterrorism. His work has been published in Science, Risk Analysis, Analytics magazine, and several other peer-reviewed journals. He is a member of the American Association for the Advancement of Science (AAAS), the Institute For Operations Research and Management Science (INFORMS), and the Society for Risk Analysis (SRA). He earned a Ph.D. in astrophysics from the University of California, Berkeley, and a Master of Advanced Study (MASt) in mathematics from Cambridge University.
Inhaltsangabe
Introduction. Elements. Lists. Uncertainty and Error. 1 Dimensional Data Sets. Related Lists and 1 Dimensional Data Sets. 2 Dimensional Data Sets. Unstructured Data Sets. Prescriptive Decision Analysis. Project Management. Communicating Analytic Findings. What to Do Next. Bibliography. Index.
Introduction. Elements. Lists. Uncertainty and Error. 1 Dimensional Data Sets. Related Lists and 1 Dimensional Data Sets. 2 Dimensional Data Sets. Unstructured Data Sets. Prescriptive Decision Analysis. Project Management. Communicating Analytic Findings. What to Do Next. Bibliography. Index.
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