Do you want to help your organisation improve productivity and enhance performance? A highly developed understanding of statistical models will do just that.

Our Advanced Statistical Analysis course has been designed to help those with a background in statistics to understand and use more advanced statistical models to make better sense of their data.

Book this team training course and through highly interactive workshops, gain a better understanding of the concepts behind advanced statistics; learn how to apply the Bayesian model and utilise more complex statistical methods, such as non-linear curves and hypothesis testing.

Practice using R programming on public sector data sets, which will help you utilise more advanced statistical methods to improve your organisation’s performance.

Learning Outcomes

  • Apply advanced statistics within your organisation
  • Use the Bayesian statistics theory to predict trends
  • Learn how to use R programming to analyse your data
  • Gain a firm understanding of advanced statistics concepts
  • Utilise advanced statistical methods to improve your organisation’s performance
All the Understanding ModernGov courses are Continuing Professional Development (CPD) certified, with signed certificates available upon request for event.

Enquire About In-House Training

To speak to someone about a bespoke training programme, please contact us:
0800 542 9414
[email protected]


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09:25 - 09:30


09:30 - 10:00

Trainer's Welcome & Clarification of Learning Objectives

10:00 - 11:00

Key Concepts behind Advanced Statistics

  • The Data Generating Process
  • Introduction to R programming
  • Review of randomness and trends
  • Establish what type of data you should be using
  • Examine real-life public-sector statistics and data
  • Gain an overview of machine learning: predictive analysis, AI and cloud computing
11:00 - 11:15

Morning Break

11:15 - 12:00

Applying the Bayesian Theory

  • Missing data
  • Known biases
  • Intuitive probability-based outputs
  • Incorporating prior evidence or opinion
  • Establish areas in modelling and imperfect data where the Bayesian theory can help
12:00 - 13:00

Workshop: Utilising Advanced Statistical Methods Part 1

  • Non-linear curves
  • Hypothesis testing
  • Confidence intervals
  • Predictive distributions
  • Multilevel models for clustered data
  • Models for different outcomes (binary events or counts)
  • Identify different methods in which statistical models can be used
13:00 - 14:00


14:00 - 16:00

Workshop: Utilising Advanced Statistical Methods Part 2

  • Helpful assumptions
  • The bias/variance trade-off
  • Models with more than one predictor
  • Interactions and non-linear functions of the predictors
  • Constructing such a model for cause and effect or prediction
16:00 - 16:15

Feedback, Evaluation and Closing Remarks