With the dawn of Big Data, it has never been more important to understand how numbers can be used and presented to give an audience a bulletproof argument. Data is all around us, and only recently we all saw the former President of the United States stumble badly, trying to explain some data relating to US COVID-19 in a press interview. Perhaps the data was right, but unless it tells a story and closes-out counterarguments then it won’t be very convincing.

The statistical treatment of data is relevant to all areas of business activity and across all management functions – whether in marketing, finance, HR, operations and logistics, and accounting, or relating to information systems and technology. Statistics in business provide evidence-based information, and this makes them an important decision support tool in management. The team at Capital City Training Ltd has put together a comprehensive business data analysis course to introduce core statistical concepts and use them practically within an organisation in an accurate and compelling way.

After all, budgets cannot be justified, spending cannot be targeted and investment decisions cannot be made on the back of spurious arguments and beliefs, often backed up by ‘gut-feeling’ and skewed by personal beliefs.

What you will learn

This program provides delegates with:

  • A solid understanding of key statistical measures and how they are determined;
  • The ability to use simple statistical sampling and inference techniques to provide compelling arguments;
  • The ability to confidently interpret and argue cases on the back of presented information;
  • A framework to question data sources and interpretation;
  • An understanding of behavioural biases – and how to spot them and avoid them; and
  • Guidance on how to present and communicate with data in a compelling way using visualisation as well as statistics.

Click here to see a detailed outline

UK Modelling

  • Session 1

    Core Data Summaries & Descriptors
    Setting the Scene
    Summarising & Describing data effectively – Exercise 1
    Summarising & Describing data effectively – Exercise 2

  • Session 2

    Making Statistical Inferences
    Confidence intervals – e.g. used in “Value at Risk”
    Hypothesis testing – a single population
    Hypothesis testing – a single propositions

  • Session 3

    Statistics for Forecasting & Planning
    Simple linear regression & correlation
    Time series models for forecasting
    Biases in interpreting data – “knowing how your brain works to avoid making mistakes!”

  • Session 4

    Data-driven Storytelling (and data-visualisation)
    This final session turns the presentation of data into an art-form, looking at data visualisation and providing delegates with a practical, fun, accessible guide for creating engaging presentations and compelling arguments.