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Statistical Methods in Data Analysis - PHY00009M

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  • Department: Physics
  • Module co-ordinator: Dr. Alessandro Pastore
  • Credit value: 10 credits
  • Credit level: M
  • Academic year of delivery: 2020-21

Module will run

Occurrence Teaching cycle
A Autumn Term 2020-21

Module aims

This module aims to convey the understanding and experience in the use of statistical methods in physics necessary for unbiased evaluation of data (either experimental or
theoretical). The module introduces advanced methods in data analysis, which includes areas of Maximum Likelihood, fitting methods, and confidence regions.

Module learning outcomes

At the end of this module successful students will be able to:

  • Describe the basic statistics involved in the analysis of physical data.
  • Demonstrate an understanding of the principles underlying data analysis.
  • Define the appropriate statistic for use in concrete fitting of data, including X ² and maximum likelihood methods.
  • Perform data fitting and evaluate the fit results, including error matrices, confidence limits and goodness-of-fit.
  • Demonstrate the use of maximum likelihood methods.
  • Evaluate confidence intervals or confidence regions in data analysis in general.


Task Length % of module mark
Physics Practice Questions
N/A 20
Open Examination (1 day)
Statistical Methods in Experimental Physics - Coursework
N/A 80

Special assessment rules



Task Length % of module mark
Open Examination (1 day)
Statistical Methods in Experimental Physics - Open book re-assessment
N/A 100

Module feedback

Information currently unavailable

Indicative reading

  • R. J. Barlow. Statistics: A guide to the use of statistical methods in the physical sciences. John Wiley & Sons, Inc., 1989.

The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.

Coronavirus (COVID-19): changes to courses

The 2020/21 academic year will start in September. We aim to deliver as much face-to-face teaching as we can, supported by high quality online alternatives where we must.

Find details of the measures we're planning to protect our community.

Course changes for new students