Applying Analytics - Levine, E. S.

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Résumé :
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Biographie:
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.

Sommaire:
Introduction What Is Analytics? What Makes an Analyst? How Is Analytics Done? Analytics in Groups Onward! Elements Introduction Stevens' Levels of Measurement Continuous and Discrete Scales Attributes Data Sets Lists Introduction Two Example Lists Elementary Analyses Additional Techniques The Normal Distribution and the Height List Hypothesis Testing and Frequency Distributions Significance of Results Discarding Data from Normally Distributed Data Sets Uncertainty and Error Introduction Definitions, Descriptions, and Discussion Quantification of Uncertainty Propagation of Uncertainty Uncertainty in the Mean Why Is This So Unsettling? 1-Dimensional Data Sets Introduction Element Spacing Three Example 1-Dimensional Data Sets Interpolation Smoothing Fitting 1-Dimensional Data Sets Increasing Local Contrast Frequency Analysis Filtering Wavelet Analysis (Advanced Topic) Related Lists and 1-Dimensional Data Sets Introduction Jointly Measured Data Sets Example 1-Dimensional Linked Data Sets Correlation Ratios Fitting Related Lists and 1-Dimensional Data Sets Correlation Functions 2-Dimensional Data Sets Introduction Example 2-Dimensional Data Sets Restructuring Data Sets Analogs of 1-Dimensional Techniques Analogs of 1-Dimensional Techniques for Related 2-Dimensional Data Sets Higher-Dimensional Data Sets Unstructured Data Sets Introduction Extracting Structure from Unstructured Data Text Mining Bayesian Techniques Prescriptive Decision Analysis Introduction Understanding the Decision Environment Determining and Structuring Objectives Identifying Alternatives Utility Functions Decision Trees Game Theory Negotiations Project Management Introduction How Analytic Projects Are Typically Managed A Methodology for Project Management Hastening Project Completion Project Management of Analytic Projects Other Project Management Methodologies Communicating Analytic Findings Introduction Fundamental Principles of Analytic Communication Medium Audience Tips for Data Visualization What to Do Next Bibliography Index Exercises appear at the end of each chapter.