Module Details |
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module. |
Title | STATISTICS FOR PHYSICS ANALYSIS | ||
Code | PHYS392 | ||
Coordinator |
Dr DE Hutchcroft Physics Dhcroft@liverpool.ac.uk |
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Year | CATS Level | Semester | CATS Value |
Session 2023-24 | Level 6 FHEQ | First Semester | 15 |
Aims |
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To give a theoretical and practical understanding of the statistical principles involved in the analysis and interpretation of data. To give practice in analysing data by computer program. To show how to write code to solve problems in data analysis. |
Learning Outcomes |
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(LO1) Knowledge of experimental errors and probability distributions |
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(LO2) The ability to use statistical methods in data analysis |
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(LO3) The ability to apply statistical analysis to data from a range of sources |
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(LO4) Using statistical information to determine the validity of a hypothesis or experimental measurement |
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(LO5) The ability to write code to analyse data sets |
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(S1) Problem solving skills |
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(S2) Numeracy |
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(S3) Digital scholarship participating in emerging academic, professional and research practices that depend on digital systems |
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(S4) IT skills |
Syllabus |
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The course will cover: Understanding how to summarise data in a few numbers and relations between variables: Mean, variance and covariance Probability theory and how to combine probabilities : Set theory and Bayes’ Theorem Probability density functions Specific probability distributions: Binomial, Poisson and Gaussian Errors and estimators: Statistical and systematic errors and the Central Limit Theorem Corrections to estimators and qualities of good estimators Fitting a distribution to data: Likelihood functions and the principle of maximum likelihood Least square fitting methods Confidence levels Hypothesis testing |
Teaching and Learning Strategies |
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Teaching Method 1 - Lecture Teaching Method 2 - Computing Classes |
Teaching Schedule |
Lectures | Seminars | Tutorials | Lab Practicals | Fieldwork Placement | Other | TOTAL | |
Study Hours |
12 |
36 |
48 | ||||
Timetable (if known) | |||||||
Private Study | 102 | ||||||
TOTAL HOURS | 150 |
Assessment |
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EXAM | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
Examination in person There is a resit opportunity. This is not an anonymous assessment. Assessment Schedule: Semester 1 | 150 | 50 | ||||
CONTINUOUS | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
coursework There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. | 0 | 50 |
Recommended Texts |
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Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. |