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Department of Physics

Data Analysis

CMP PG Course – Module 1 Materials physics: principles, methods & analysis I

Module Component - Data Analysis

Credits

15

Tied to

F3A001 (PhD Physics) , F3A006 (MPhil Physics), F3A009 (MScR Physics)

Aims

  • To impart an understanding of the ideas, the mathematical methods and the numerical techniques of graduate-level data analysis. To acquire ability in applying the theory and practice of this knowledge to experimentally or computationally derived data sets.
  • To understand the methodology of least-squares fitting, and being able to explain the concept of a “good fit”, qualitative and quantitative; to be familiar with hypothesis testing making use of the chi-squared statistic.
  • To provide the framework that will allow experimentalists and theorists alike to answer questions such as “do the experimental results agree with the theory”, “does the theory agree with the experimental results”, and for theorists “which model works best”.

Content

  • Review of elementary statistical concepts
  • Central Limit Theorem
  • Functional approach to error propagation
  • Weighted least squares fitting
  • Least-squares fitting of complex functions
  • Computer minimisation and the error matrix
  • Hypothesis testing—how good are our models?

Learning Outcomes

Subject-specific Knowledge:

  • Students will master a body of knowledge from the following topics: Random errors in measurements; Uncertainties as probabilities; Error propagation; definitions of good-fit criteria.

Subject-specific Skills:

  • Advanced error propagation
  • Hypothesis Testing for a discrete distribution
  • Hypothesis Testing for a continuous distribution
  • Data reduction and visualization

Key Skills:

  • Problem solving, written and graphical presentation of an argument
  • The ability to select which technique is most appropriate to tackle specific problems

Teaching Methods and Contact Hours

Activity

Number

Frequency

Duration

Total/Hours

Lectures

8

1 per week

1 hour

8

Preparation, reading and homework

42

Total

50

Summative Assessment

Component: Continuous Assessment

Component Weighting: 100%

Element

Length / duration

Element Weighting

Resit Opportunity

Continuous Assessment

100%