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Cover

Mathematical Underpinnings of Analytics

Theory and Applications

Peter Grindrod

27 November 2014

ISBN: 9780198725091

276 pages
Hardback
234x156mm

Price: £42.99

A cutting edge graduate level book on the way the mathematical analytics of big data can add value and bring competitive advantage to consumer-facing industries.

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Description

A cutting edge graduate level book on the way the mathematical analytics of big data can add value and bring competitive advantage to consumer-facing industries.

  • Emphasis on analytics for customer-facing industries
  • Wide range of technical topics
  • Realistic commercial illustrations and examples
  • Strong focus of human behaviour
  • Highlights social media and peer-to-peer communications, digital media, and marketing
  • Mix of theory, applications, and commentary and advice based on hard won experience
  • First book to explain the subject from a mathematical standpoint

About the Author(s)

Peter Grindrod, Professor of Mathematics, Mathematical Institute, University of Oxford

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 EPSRC and Chair of the EPSRC's User Panel. He authored Patterns and Waves (OUP 1991, 2nd edn 1996) and has been awarded a CBE for his contribution to mathematics R&D. In 1998 he was co-founder and Technical Director of a start-up company, Numbercraft Limited, supplying analytics services and software to retailers and consumer goods manufacturers. He is a co-founder of Cignifi Inc, a Boston-based company that uses mobile phone records to provide behaviour based credit referencing for pre pay customers in emerging economies. He is a founder of Counting Lab Ltd, a UK-based start-up translating state of the art mathematics into prototype products and services.

Table of Contents

    Introduction: The Underpinnings of Analytics
    1:Similarity, Graphs and Networks, Random Matrices and SVD
    2:Dynamically Evolving Networks
    3:Structure and Responsiveness
    4:Clustering and Unsupervised Classication
    5:Multiple Hypothesis Testing Over Live Data
    6:Adaptive Forecasting
    7:Customer Journeys and Markov Chains
    Appendix: Uncertainty, Probability and Reasoning

Reviews

"It is an essential read for any mathematician" - Alan Stevens, Mathematics Today

"There is a great need for this book, which connects the typical analytical problems that organizations face with the underlying maths and statistics to solve them. Grindrod communicates his deep expertise ... for executives who want to understand the math underlying their businesses, and the quant geeks who want to know the business problems they are capable of addressing" - Thomas H. Davenport, Babson College, MIT Fellow, Author of Competing on Analytics and Big Data @ Work

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