Foundations of Data Analysis (F3229)
15 credits, Level 4
Autumn teaching
On this module, you’ll cover topics including:
- dimensions and units
- estimation of uncertainties
- introduction to computer-based data analysis
- mean, standard deviation and standard error
- error propagation
- histograms and manipulation of distributions
- the Gaussian distribution
- chi squared and (straight) line fitting
- identifying and dealing with systematics
- assessing data quality
- introduction to electrical circuits and circuit simulation.
Teaching
49%: Lecture
24%: Practical (Workshop)
27%: Seminar
Assessment
100%: Coursework (Portfolio, Presentation)
Contact hours and workload
This module is approximately 150 hours of work. This breaks down into about 40 hours of contact time and about 110 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.
We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2024/25. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum.
We’ll make sure to let you know of any material changes to modules at the earliest opportunity.
Courses
This module is offered on the following courses:
- Astrophysics MPhys
- Mathematics with Data Science BSc
- Mathematics with Data Science MMath
- Physics (Quantum Technology) (research placement) MPhys
- Physics (Quantum Technology) MPhys
- Physics (research placement) MPhys
- Physics (with an industrial placement year) BSc
- Physics (with an industrial placement year) MPhys
- Physics BSc
- Physics MPhys
- Physics with Astrophysics BSc
- Physics with Astrophysics MPhys
- Physics with Data Science BSc
- Physics with Data Science MPhys
- Theoretical Physics BSc
- Theoretical Physics MPhys