Mathematical Underpinnings of Analytics: Theory and Applications for Data Science in Customer-Facing Industries by Peter GrindrodMathematical Underpinnings of Analytics: Theory and Applications for Data Science in Customer-Facing Industries by Peter Grindrod

Mathematical Underpinnings of Analytics: Theory and Applications for Data Science in Customer…

byPeter Grindrod

Paperback | December 8, 2014

Pricing and Purchase Info

$62.95 online 
$69.95 list price save 10%
Earn 315 plum® points
Quantity:

Ships within 1-3 weeks

Ships free on orders over $25

Not available in stores

about

Analytics is the application of mathematical and statistical concepts to large data sets so as to distil insights that offer the owner some options for action and competitive advantage or value. This makes it the most desirable and valuable part of big data science.Driven by the increased data capture from digital platforms, commercial fields are becoming data rich and analytics is growing in many sectors. This book presents analytics within a framework of mathematical theory and concepts building upon firm theory and foundations of probability theory, graphsand networks, random matrices, linear algebra, optimization, forecasting, discrete dynamical systems, and more. Following on from the theoretical considerations, applications are given to data from commercially relevant interests: supermarket baskets; loyalty cards; mobile phone call records; smart meters; "omic" data; sales promotions; social media; and microblogging. Each chapter tackles a topic in analytics: social networks and digital marketing; forecasting; clustering and segmentation; inverse problems; Markov models of behavioural changes; multiple hypothesis testing and decision-making; and so on. Chapters start with background mathematical theory explainedwith a strong narrative and then give way to practical considerations and then to exemplar applications. Exercises (and solutions), external data resources, and suggestions for project work are given. The book includes an appendix giving a crash course in Bayesian reasoning, for both ease and completeness.
Peter Grindrod researches a range of topics in analytics for customer-facing industries and in particular for the digital society. He is in an almost unique position of having experience within commercial settings as well as within academia. He is a former President of the Institute of Mathematics and its Applications, member of the E...
Loading
Title:Mathematical Underpinnings of Analytics: Theory and Applications for Data Science in Customer…Format:PaperbackDimensions:280 pages, 9.21 × 6.14 × 0 inPublished:December 8, 2014Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0198725094

ISBN - 13:9780198725091

Reviews

Table of Contents

Introduction: The Underpinnings of Analytics1. Similarity, Graphs and Networks, Random Matrices and SVD2. Dynamically Evolving Networks3. Structure and Responsiveness4. Clustering and Unsupervised Classication5. Multiple Hypothesis Testing Over Live Data6. Adaptive Forecasting7. Customer Journeys and Markov ChainsAppendix: Uncertainty, Probability and Reasoning