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MPhys Physics

Year of entry: 2021

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

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