# BSc Physics with Theoretical Physics / Course details

Year of entry: 2023

## Course unit details:Introduction to Data Science

Unit code PHYS10792 10 Level 1 Semester 2 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 10%
Written exam 90%

* Other = Online quizzes.

### Feedback methods

Feedback is through exercises (via online feedback) and the exam.

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 24
Independent study hours
Independent study 74.5

### Teaching staff

Staff member Role
Marco Gersabeck Unit coordinator
Rene Breton Unit coordinator