Mathematics & Statistics

Dr Jonathan Gillard is a Reader in Statistics at Cardiff University, Senior Fellow of the Higher Education Academy, and a member of the Statistics Interest Group of sigma: the UK network for excellence in mathematics and statistics support. He has taught statistical inference to mathematics undergraduates and postgraduates for over 10 years. Jonathan maintains a strong interest in innovative teaching methods, being an editorial board member of MSOR Connections. He is an active researcher of the theory of statistics and is currently working on a number of collaborative projects with the Office for National Statistics and National Health Service. His recent publications have included work on using regression in large dimensions, novel methods for forecasting, and new approaches for learning about the performance of machine learning algorithms.

Advances in Business Statistics, Methods and Data Collection  delivers insights into the latest state of play in producing establishment statistics, obtained from businesses, farms and institutions. Presenting materials and reflecting discussions from the 6th International Conference on Establishment Statistics (ICES-VI), this edited volume provides a broad overview of methodology underlying current establishment statistics from every aspect of the production-life cycle while spotlighting innovative and impactful advancements in the development, conduct, and evaluation of modern establishment statistics programs. Highlights include:

Dipankar De ,  PhD , received his BSc and MSc in mathematics from the University of Calcutta, India and his PhD in mathematics from Tripura University, India. He has over 40 years of teaching experience and is an associate professor and guest lecturer in India. He has published many research papers in various reputed journal in the field of fuzzy mathematics and differential geometry.

Ready to build quantum computing applications using Q# and the Microsoft Quantum Development Kit? This is the book for you.

Erwin O. Kreyszig (January 6, 1922 in Pirna, Germany – December 12, 2008) was a German Canadian applied mathematician and the Professor of Mathematics at Carleton University in Ottawa, Canada. He was a pioneer in the field of applied mathematics: non-wave replicating linear systems. He was also a distinguished author, having written the textbook Advanced Engineering Mathematics, the leading textbook for civil, mechanical, electrical, and chemical engineering undergraduate engineering mathematics.

This book is part of a series of textbooks created for the new Cambridge International Examinations (CIE) mathematics syllabus. The authors have worked with CIE to assure that the content matches the syllabus and is pitched at a suitable level. Pure Mathe

Francisco Juretig has worked for over a decade in a variety of industries such as retail, gambling and finance deploying data-science solutions. He has written several R packages, and is a frequent contributor to the open source community.

An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization.

The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

Hadley Wickham  is  Chief Scientist at RStudio and a member of the R Foundation. He builds tools (both computational and cognitive) that make data science easier, faster, and more fun. His work includes packages for data science (ggplot2, dplyr, tidyr), data ingest (readr, readxl, haven), and principled software development (roxygen2, testthat, devtools). He is also a writer, educator, and frequent speaker promoting the use of R for data science.       

This is a text with more than enough material for a one-semester introduction to combinatorics.

Henry Bequet is Director of High-Performance Computing and Machine Learning in the Financial Risk division of SAS. In that capacity, he leads the development of a high-performance solution that can run SAS code on thousands of CPU and GPU cores for advanced models that use techniques like Black-Scholes, Binomial Evaluation, and Monte-Carlo simulations.