.jpg)
Apply through UCAS
- UCAS course code
- F305
- UCAS institution code
- M20
Course unit details:
Introduction to Data Science
Unit code | PHYS10791 |
---|---|
Credit rating | 10 |
Unit level | Level 1 |
Teaching period(s) | Semester 1 |
Offered by | Department of Physics & Astronomy |
Available as a free choice unit? | No |
Overview
Introduction to Data Science
Aims
- To introduce basics of statistical methods and modern day advanced data analysis techniques, as required in all fields working with data.
- To deepen the understanding of how data analysis works for small and large data samples.
- To obtain a comprehensive set of tools to analyse data.
Learning outcomes
This course unit detail provides the framework for delivery in 20/21 and may be subject to change due to any additional Covid-19 impact. Please see Blackboard / course unit related emails for any further updates
On completion successful students will be able to:
- Demonstrate an understanding of the basics of the statistical analysis of data.
- Explain methods of data analysis and their idea.
- Apply a set of analysis techniques as required for basic and advanced datasets.
- Critically assess new results derived from datasets.
- Use the knowledge of statistical data analysis to understand more advanced and new techniques.
Syllabus
- Probabilities and interpretations
- Probability distributions
- Parameter Estimation
- Maximum Likelihood and extended maximum likelihood
- Least Square, chi2, correlations
- Monte Carlo basics
- Probability and confidence level
- Hypothesis testing
- Goodness of fit tests
- Limit setting
- Introduction to Multivariate Analysis Techniques
Assessment methods
Method | Weight |
---|---|
Other | 20% |
Written exam | 80% |
Feedback methods
Feedback is through exercises (via online feedback) and exam.
Recommended reading
Barlow, R., Statistics - A Guide to the Use of Statistical Methods in the Physical Sciences, Wiley
Cowan, G., Statistical Data Analysis, Oxford
Behnke, O., et al, Data Analysis in High Energy Physics: A Practical Guide to Statistical Methods, Wiley
Study hours
Scheduled activity hours | |
---|---|
Assessment written exam | 1.5 |
Lectures | 22 |
Independent study hours | |
---|---|
Independent study | 76.5 |
Teaching staff
Staff member | Role |
---|---|
Marco Gersabeck | Unit coordinator |
Rene Breton | Unit coordinator |