PHY1030 Practical Physics and IT Skills 2023-24
Dr J. Hatchell and Prof. V.V. Kruglyak
Delivery Weeks: T1:01-05,07-12, T2:01-11
Level: 4 (NQF)
Credits: 15 NICATS / 7.5 ECTS
Enrolment: 14 students (approx)


The practical laboratory work section of this module provides a broad foundation in experimental physics, upon which experimental work for the Stage 2 year and project work in Stage 3 builds. It starts with a short series of lectures, supplemented with problems sets, on error analysis and graph plotting. Laboratory work is normally undertaken in pairs, with support from demonstrators. Experiments are recorded in lab-books and presented as formal reports. One of the experiments involves working as a larger group.

In the IT Skills section of this module students learn to use Python for scientific applications. Python is an interpreted, high-level, general-purpose programming language that can be used for a range of academic and research-based activities including high level mathematics and data processing work. Python is widely used in commercial and research environments.

The PHY0000 Communication and Key Skills course held in 'Opportunities Week', i.e. T1:06 constitutes the the third section of this module.

Module Aims

Every physicist must be able to analyse data, evaluate theoretical models, and present their work in the form of a technical report. They must also be able to perform investigations, such as experiments, and solve the problems they encounter in a systematic and logical manner.

Experimentation is one of the central activities of a scientist. Experimental observations form the bases for new hypotheses and also test scientific theories. In this module, you will learn to understand and apply the experimental method, develop your ability to make reliable measurements and report them in an effective and ethical manner.

Intended Learning Outcomes (ILOs)

A student who has passed this module should be able to:

Syllabus Plan

Part A: Practical Laboratory

Each experiment is described in a brief laboratory script and a short video. General guidance on experiments, data analysis and result reporting is provided in the Laboratory Manual.

General supervision and assistance are available from the demonstrators during the time-tabled practical sessions. Each demonstrator conducts the initial discussion with and monitors the progress of the assigned students, taking a pastoral role and reporting any problems to the Module Coordinator. Feedback is given on each experiment during a 15-minute final discussion with a demonstrator. For the oral presentation in the Student Conference, the assessment is made by demonstrators with partial input from the students.

Note: The Communication and Key Skills content and activities are described in the PHY0000 component description.

Part B: IT Skills

  1. Introduction to Python
    1. Running interactive Python; loading modules and packages; using Python as a graphical calculator; simple calculations, maths, simple functions and plotting.
    2. Using Jupyter notebooks with Numpy and Matplotlib.
  2. Core Python programming
    1. Objects, variables and assignments. Dynamic 'Duck' typing. Numerical datatypes.
    2. More datatypes: strings, lists, tuples, and dictionaries.
    3. Control flow I: Conditionals, comparisons and Boolean logic.
    4. Control flow II: Loops.
    5. Functions: keyword and positional arguments, default arguments, *args and **kwargs, docstrings, variable scope.
    6. Program structure and documentation, error handling, testing and debugging.
  3. Python for labs
    1. Numpy arrays and datatypes.
    2. Using Numpy for reading and writing data; simple statistics; plotting data with errorbars.
    3. Fitting a straight line with a least-squares fit.
    4. Nonlinear least-squares fitting with Scipy.
    5. Publication-quality plots with Matplotlib: multiple axes, control of plot elements.

Learning and Teaching

Learning Activities and Teaching Methods

Description Study time KIS type
3×1-hour data analysis lectures 3 hours SLT
10×1-hour computing lectures 10 hours SLT
3×2-hour self-study packages (problem sets) 6 hours GIS
11×2-hour computer laboratory sessions (IT) 22 hours SLT
5×4-hour computing homework 32 hours GIS
10×3-hour practical laboratory sessions 30 hours SLT
6-hour student conference 6 hours SLT
3×1-day communications skills workshops 21 hours SLT
Reading and private study 20 hours GIS


Weight Form Size When ILOS assessed Feedback
0% Data analysis homework Three 2-hour problems sets (quizzes) Week T1:02 4, 14 Written and verbal
0% 10×Python classwork assignments (formative) 4 hours In class 1, 13, 15-17 Written and verbal
50% 5×computing homework assignments 4 hours per assignment Deadline Monday week T1:03,05,08,10,12 1, 13, 15-17 Written and verbal
10% Experiments, recorded in the notebook Two notebook assessments ca 4-week intervals in T1:01-05, 06-12 2-9, 11-14, 16, 17 Written and verbal
20% Experiments, written up as formal experiment reports Two 1250-word reports ca 4-week intervals in T2:01-11 2-9, 11-14, 16, 17 Written and verbal
10% Group oral presentation for the Student Conference 20 minutes Week T2:11 10, 11 Written and verbal
10% Communications and key skills component PHY0000 3 days Week T1:06 18 Written and verbal

Notes: Refer to the Undergraduate Handbook for details and marking criteria. Briefly, laboratory notebooks and reports are marked in one-to-one discussion between the student and a demonstrator; oral presentations involve both demonstrator and moderated peer assessment.


The following list is offered as an indication of the type & level of information that students are expected to consult. Further guidance will be provided by the Module Instructor(s).

Core text:

Supplementary texts:


Further Information

Prior Knowledge Requirements

Pre-requisite Modules none
Co-requisite Modules Vector Mechanics (PHY1021), Waves and Optics (PHY1023) and Properties of Matter (PHY1024)


Re-assessment is not available except when required by referral or deferral.

Original form of assessment Form of re-assessment ILOs re-assessed Time scale for re-assessment

Notes: Re-assessment is not available for this module.

KIS Data Summary

Learning activities and teaching methods
SLT - scheduled learning & teaching activities 92 hrs
GIS - guided independent study 58 hrs
PLS - placement/study abroad 0 hrs
Total 150 hrs
Summative assessment
Coursework 70%
Written exams 0%
Practical exams 30%
Total 100%


IoP Accreditation Checklist
  • XX-01 Experimental work in a practical laboratory
  • XX-02 IT Skills
Availability unrestricted
Distance learning NO
Keywords Physics; Data; File; Experience; Function; Laboratory; Stage; Errors; Methods; Python; Analysis.
Created 01-Oct-10
Revised 29-Sep-22