Core statistics
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Event details
Sessions
- 19 April 2027 — 09:30 to 17:30 — Craik-Marshall
- 20 April 2027 — 09:30 to 17:30 — Craik-Marshall
- 21 April 2027 — 09:30 to 17:30 — Craik-Marshall
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About the course
A practical introduction to statistical analysis for researchers working with biological and experimental data.
This course teaches how to choose, run, and interpret common statistical analyses using R or Python. The focus is on practical application rather than statistical theory, with hands-on exercises throughout.
Topics include hypothesis testing, ANOVA, regression, linear models, model selection, and power analysis.
By the end of the course, participants should be able to:
- analyse datasets using standard statistical techniques
- select appropriate statistical tests for different research questions
- understand the assumptions and limitations of common methods
- carry out statistical analyses confidently in R or Python
Teaching is primarily hands-on, with short lectures introducing key concepts and methods.
Intended audience
This course is suitable for:
- researchers and students working with biological or experimental data
- participants who already have basic familiarity with either R or Python
- anyone looking for a practical foundation in statistical analysis
Prerequisites
If you are completely new to programming, introductory training in R or Python is essential before attending.
Related courses:
- Data analysis in R
- Python
- Core statistics
Course fees
All fees are per full training day
| Category | Fee |
|---|---|
| Industry full charge | £130.00 |
| Academic / Government / charity concessionary | £65.00 |
| Cambridge University staff members / postdocs / visitors | £65.00 |
| Cambridge University registered students | Free |
| Special events | Per event |
Payment options will be provided in booking confirmation emails sent after registration.