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Mathematics and Statistics Training



4 days16 hrs VILT, 12 hrs self-paced


Virtual Learning


About This Course

There are many training courses on statistics and statistical analysis, but very few that focus specifically on the application of these techniques to pharmaceutical manufacture and control. This course does.

Taught by statisticians and pharmaceutical industry professionals, our four-day course is designed to meet the needs of the aspiring Qualified Person (QP) and other pharmaceutical professionals. The highly participative training teaches you how to use statistical techniques to assess and monitor:

  • The reliability and accuracy of data you generate
  • The capability and reliability of the processes you work with every day

The pharmaceutical industry has historically underutilized the same statistical data analysis techniques many other industries have extensively used to drive product and process improvement. Even today, the pharmaceutical industry could still be characterized as data rich but information poor.

The provision of useful information is essential. That is why we created this pharmaceutical mathematics and statistics training course.

Recent developments in global Good Manufacturing Practice (GMP) guidelines are urging pharmaceuticals to catch up with other industries by placing greater emphasis on the trending of data. This applies to EU and U.S. requirements for ongoing process verification as part of process validation, product quality reviews, ICH Q10 and more. The ability to analyze and trend data is now an essential survival skill. This pharmaceutical training course shows you how to do this simply and effectively.

Our virtual instructor-led training will be delivered via a combination of live instructor-led virtual classrooms and self-paced learning online. Full details will be sent to you following registration.

This course is approved by the Royal Society of Chemistry as suitable for its members’ continuing professional development.

Key Learning Objectives

At the end of this course, you will understand how to:

  • Assess the reliability and accuracy of data and information arising from samples taken from a population, using techniques such as:
    • Basic statistics: mean, standard deviation, etc.
    • Histograms
    • Box plots
    • Confidence intervals
  • Monitor and detect adverse trends before a process goes out of control, using:
    • Control charts: Shewhart, mean and range, cumulative sum control chart (CUSUM) and attribute charts
    • Linear regression
  • Assess the capability and reliability of a process
  • Use and know the limitations of acceptance testing using ISO 2859
  • Compare results using:
    • T-tests
    • Analysis of variance (ANOVA)
  • Interpret the interaction of process parameters via experimental design and multivariate analysis
  • Maintain regulatory compliance

Course Outline

Basic Statistical Quantities

  • Terminology and definitions
  • Measures and visual plots to describe populations and samples
  • Deciding how much data to collect to enable appropriate decision making

Statistical Techniques

  • Data visualization tools:
    • Histograms
    • Box plots
  • Confidence and tolerance intervals
  • Statistical process control (SPC) tools:
    • Individuals, Shewhart, CUSUM and attribute control charts
    • Pareto charts
    • Fishbone diagrams
    • Process capability (capability potential (Cp) and centered process capability (CpK)
  • ISO 2859 specification for sampling procedures and tables, application of sampling by attributes
  • Regression analysis
  • Statistical testing:
    • The t-test
    • ANOVA
    • Outlier testing
    • Non-parametric methods
  • Experimental design
  • Multivariate analysis

Practical Application of Statistical Techniques

  • Practical examples of the application of statistical techniques using teamwork sessions
  • Experience of the application of statistical techniques in a quality assurance (QA) system in a manufacturing environment
  • The role of computers in the application of statistical techniques
  • Six Sigma: Definition and benefits

Who Should Attend

The Aspiring Qualified Person

  • Our pharmaceutical mathematics and statistics training is generally considered the best available and our QPs are held in high regard within the industry
  • As well as being accepted in the UK, our training courses are well known and accepted by several EU countries including Ireland, the Netherlands, Austria, Hungary and Malta
  • You are more likely to become a QP with us than with any other training provider

The Pharmaceutical Technical Professional

  • Not all people attending these courses intend to become QPs. Many use the training to develop as technical managers in other areas of pharmaceutical manufacture and control
  • Many industry professionals from a range of disciplines attend the courses as part of their continuing professional development. Taken with some of our other QP modules, this course is designed to lead to postgraduate certificate, diploma and MSc qualifications

Course Tutors

Course tutors will be selected from the following:

Peter Gough - Peter is an analytical chemist with over 40 years’ industry experience in applying statistical techniques to pharmaceutical manufacturing, testing and quality management.

David Young – David is a senior lecturer in the Department of Statistics and Modelling Science, University of Strathclyde who has carried out statistical consultancy work for the NHS, pharmaceutical companies and Health Protection Scotland.


Multi-delegate discounts available. Discounts also offered to NHS staff and charities.

Qualified Person Training With NSF

Watch the video
  • Good course. Will allow me to get more use out of the reams of data we generate.
    Tim Johnson
    Aeropak Chemical Products, UK
  • Really good mix of exercises/tasks and theory to make sure that we understand how to apply the different models.
    Anna Jessen
    Cook Regentec, Denmark
  • Delivery of material by David was excellent and made what I thought was going to be a very difficult subject easier to understand and relate to the role of a QP.
    Dawn Douglas
    Almac, UK

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