Statistics

School of Statistics & Information Modelling (SIM)

The School of Statistics & Information Modelling covers such remits as:

  • Applied Statistics – all topics e.g. probaility theory, statistical inference, time series, multivariate analysis, biostatistcs and epidemiology, experimental design, operational research, demography, six-sigma methodology and total quality management, etc.
  • Stochastic Processes and their Applications, especially in Business and Finance;
  • Statistical Modelling & Informatics;
  • Industrial statistics: Six-Sigma Methodology, Statistical Quality Control, and Total Quality Management for products and services;
  • Biostatistics/Clinical Research Organisations-focused research and consulting/Health Economics Modelling;
  • Wider perspectives from Science, Technology, Engineering & Mathematics (STEM subjects);
  • Wider perspectives from Health and Well-Being;
  • Wider perspectives from Complex Systems, including Complexity Science, Scenario Modelling, Theoretical Physics, Superforecasting, and Futurology;
  • Synergies with Quantitative Social Sciences & Humanities;
  • Statistics and Information Modelling in Society.

Related Spin-off

  • Sigma-Z Consulting, see www.sigma-zconsulting.com: Again, work in this school produces outstanding corporate academic PhD theses, MSc dissertations, and advanced project outcomes, which can be spun-off as social enterprises, and for-profit born-global firms that are powered by the Internet.
  • Oselux Institute for Statistics, Information Modelling and Financial Mathematics (SIMFIM): which combines techniques in applied statistics, global economics and financial mathematics to address emerging hot topics and challenges in global economics and capital management, including innovative and technology-enhanced business analytics, business analysis, data science, fintechs, algorithmic capital management, structured finance, data-driven decision making, simulations, and use of these techniques and theory of constraints in creative problem-solving.