Intermediate Statistics (in-person)
Dr Maria Christodoulou & Oxford University Statistical Consulting (OxUSC)
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.
COURSE DETAILS
The course consists of a three hour class, 09.00 - 12.00, every Tuesday of Hilary Term 2024.
The course will enable the analysis of continuous, binary, ordinal, count outcomes, mixed effect setups, and longitudinal data analysis.
Pre-requisites for attending the course:
- Basic Inference.
- Hypothesis testing.
- Basic linear regression.
- Basic graphics.
- Interpretation of modelling outputs.
LEARNING OUTCOMES
By the end of this course participants will:
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Be able to model continuous outcomes by means of a linear progression, to assess fit and usability through checking assumptions, and to present results and accurately interpret model summaries.
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Have developed an understanding of the Generalised Linear Model framework.
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Be able to model binary outcomes by means of a Logistic regression, to assess fit and usability through checking assumptions, and to present results and to accurately interpret model summaries.
INTENDED FOR
DPhil students and research staff with prior knowledge of statistical tools and approaches, and who need them for their research. PLEASE CHECK YOU MEET THE PRE-REQUISITES ABOVE.
NUMBER OF PLACES
30
COURSE LEADER
Dr Maria Christodoulou & Oxford University Statistical Consulting (OxUSC)
TIME / Date
09.00 - 12.00 | 16th January 2024
09.00 - 12.00 | 23rd January 2024
09.00 - 12.00 | 30th January 2024
09.00 - 12.00 | 6th February 2024
09.00 - 12.00 | 13th February 2024
09.00 - 12.00 | 20th February 2024
09.00 - 12.00 | 27th February 2024
09.00 - 12.00 | 5th March 2024
BOOKING INFORMATION
IMPORTANT: BEFORE BOOKING A PLACE ON THIS COURSE PLEASE CHECK THAT YOU MEET THE COURSE PRE-REQUISITES SET OUT ABOVE.
To book your place on Intermediate Statistics please click here.
TERMS & CONDITIONS
When registering for this course, please check our Terms and Conditions.
RDF SKILLS
A1, A2
The Researcher Development Framework (RDF) provides a framework for planning and supporting the personal, professional and career development of graduate students and research staff. See the the following for more details:
The Researcher Development Framework page
The Researcher Training Tool (click on Researcher Development)
Vitae (Vitae is a national organisation dedicated to realising the potential of researchers through supporting their professional and career development.)