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Six Oxford University academics, including three from MPLS Division, have been elected to the prestigious Fellowship of the Royal Society.
Beginners Statistics with R (in-person)
All DPhil students Research staff Statistics
Tuesday, 23 April 2024, 9.30am to 12.30pm
This course will provide an introduction to basic statistical concepts, methods and tools for scientific research.
Intermediate Statistics (in-person)
All DPhil students Research staff Statistics
Tuesday, 16 January 2024, 9am to 12pm
This course aims to provide solid foundations to implementing linear regression, three types of Generalised Linear Models, and hierarchical models.
Introduction to Bayesian Statistics (in-person)
All DPhil students Research staff Statistics
Friday, 26 January 2024, 9.30am to 5pm
This course aims to provide solid foundations to implementing linear regression, three types of Generalised Linear Models, and hierarchical models.
Applying Bayesian Statistics using Stan (in-person)
All DPhil students Research staff Statistics
Wednesday, 31 January 2024, 9.30am to 5pm
This course aims to provide solid foundations to implementing linear regression, three types of Generalised Linear Models, and hierarchical models.
Open Science (in-person)
All DPhil students Research staff Statistics
Thursday, 01 February 2024, 9am to 5pm
Beginners Statistics with R (in-person)
All DPhil students Research staff Statistics
Tuesday, 10 October 2023 to Tuesday, 05 December 2023, 9am - 12pm
This course will provide an introduction to basic statistical concepts, methods and tools for scientific research.
Introduction to statistical inference using R
All DPhil students Research Research staff Statistics
Wednesday, 18 January 2023 to Wednesday, 08 March 2023, 2pm - 5pm
This course will provide an introduction to statistical inference and basic commands using R. This is most suitable for complete beginners or those requiring foundational statistics refresher. Topics covered include: hypothesis testing, basic statistical testing procedures, linear regression, base R, and introduction to the tidyverse suite of R packages.