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This course is delivered by Dr Jake AylmerProfessor Ted Shepherd and Dr Ben Harvey. It runs from October to December 2024.

You will learn statistical methods and reasoning relevant to environmental science. You'll also gain experience in the proper use of statistics for the analysis of weather and climate data. Practical classes use Python. The topics are:

  • Introduction to statistics: basic concepts, history
  • Exploratory data analysis: summary statistics
  • Forecast verification: skill scores
  • Linear regression: correlation
  • Multiple regression: confounders, causality
  • Time series analysis: autocorrelation
  • Concepts of probability: Bayes theorem
  • Probability distributions: lots of different distributions!
  • Parameter estimation: confidence intervals
  • Hypothesis testing: significance tests, p-value.

This course is developed from the Statistics for Weather and Climate Science module.

There are practical assignments each week (10 in total) and four of these will be assessed.

Provisional Online Timetabled sessions, Wednesdays, 2-4pm (UK time)

2 October 2024, 14:00–16:00
 9 October 2024, 14:00–16:00
16 October 2024, 14:00–16:00
23 October 2024, 14:00–16:00
30 October 2024, 14:00-16:00

No class on 6 November

13 November, 14:00–16:00
20 November, 14:00–16:00
27 November, 14:00–16:00
 4 December 14:00–16:00
11 December 14:00-16:00

A joining link will be given to enrolled learners.


Working knowledge of A-level Mathematics

Equivalent to Further Mathematics A-level or a pass equivalent to a 2.1 in a first year science undergraduate mathematics module.

Programming experience (ideally Python). Standard equivalent to a first year science undergraduate programming module.

Read the Terms and Conditions for Meteorology Online Courses


Apply by 9 September 2024.

Further Learning

Find out about the Department of Meteorology, the scheduled online courses and the open online courses.