PH12004: Physics skills 1
[Page last updated: 03 June 2024]
Academic Year: | 2024/25 |
Owning Department/School: | Department of Physics |
Credits: | 15 [equivalent to 30 CATS credits] |
Notional Study Hours: | 300 |
Level: | Certificate (FHEQ level 4) |
Period: |
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Assessment Summary: | CWPI 10%, CWRI 25%, CWSI 40%, PR 25% |
Assessment Detail: |
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Supplementary Assessment: |
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Requisites: | |
Learning Outcomes: |
While taking this unit the student should be able to:
demonstrate the correct use of a range of standard laboratory equipment to plan and conduct small-scale experiments;
use a log-book to make an accurate and effective record of their experiments, present results and detail the analysis of their results;
effectively and accurately communicate scientific work both orally and in writing in formal and informal contexts;
demonstrate an understanding of a range of statistical operations such as error analysis and least squares fitting and use them to analyse experimental data;
use high-level programming language Python to solve scientific problems and perform a variety of data analyses and visualisations;
demonstrate a stepwise systematic approach to tackle open-ended physics problems. |
Synopsis: | Experimental laboratory work, scientific computing, the understanding of measurement, data & applied statistics, scientific writing, presentation and problem solving are skills that are fundamental to your development as a physicist. You will work individually and in groups to advance your confidence and competence in these key areas, to provide a platform for higher-level project work in future years. |
Content: | Experimental laboratory (72 hours)
Techniques of measurement: Examples include use of oscilloscope, light sources and detectors, operational amplifiers, geometrical optics, introduction to computer data acquisition.
Demonstrations: Examples include velocity of light, astrophysical data analysis, elastic properties, spectrum of atomic hydrogen, ultrasonic waves in air, the Michelson interferometer, heat engines, and photoelectric determination of Planck's constant.
Electronics: Resonant ac circuits and filters. Operational amplifiers.
Project: Two independent projects to simulate the processes of researching, planning, performing, analysing and reporting a small-scale experimental investigation. The topics are chosen from a wide range of physics and astrophysics topics appropriate to first-year students, including hypothesis testing, design of apparatus and investigating unfamiliar phenomena.
Scientific computing (36 hours PC labs & lectures)
Semester 1: Introduction to Python; data and plotting in Python; basic data analysis and fitting; further data analysis and fitting. There will be about 18 hours of classes per student (mostly PC lab sessions) which will be completed in the first few weeks of semester 1, before the lab sessions start. It will be the same for Physics/PwA/PwTP students and would also be appropriate for M&P and NS students.
Semester 2: Further development of Python programming, using problem-based activities linking numerical techniques with applications.
Scientific writing and presentation (12 hours)
Scientific report writing: abstract, introduction, method, discussion, conclusion and referencing. Using Microsoft Word and LaTeX, including for mathematical typesetting. Writing up solutions to Physics and Maths problems, including developing a logical argument and correctly incorporating maths into writing. Presenting scientific talks and posters.
Problem solving (15 hours)
Developing good approaches to problem-solving, and facilitating students to evaluate critically their problem-solving methods and techniques. Lectures, worked examples and class exercises will cover both more narrowly set and more open-ended problems.
Measurement, data & applied statistics (15 hours)
Dimensional analysis, and orders of magnitude (dimensional homogeneity, Rayleigh Method). Describing data distributions, and estimating uncertainty (mean, variance, standard deviation). Combining errors, Gaussian errors as a consequence of the Central Limit Theorem. Linear regression (least squares; error in the gradient and intercept).
Measurements; sources and types of uncertainties and errors; probability distributions and basic statistics; fitting and its limitations; model comparison; degrees of freedom; signal-to-noise; biases; selection effects; correlations; closing the loop - how to reduce uncertainties; visualising data. These topics will be taught first using simulated data, with the students progressing to problems involving real data sets. |
Course availability: |
PH12004 is a Must Pass Unit on the following courses:Department of Physics
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Notes:
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