Accessibility statement

Mathematical, Computational & Professional Skills 1 - PHY00031C

« Back to module search

  • Department: Physics
  • Module co-ordinator: Dr. Kate Lancaster
  • Credit value: 20 credits
  • Credit level: C
  • Academic year of delivery: 2024-25
    • See module specification for other years: 2023-24

Module summary

Mathematical, Computational & Professional Skills 1 will link the mathematical skills you gained before university to applications in physics. It will take your existing knowledge of calculus and algebra, deepening your understanding such that you develop the skills which will be needed for physics modules throughout your degree. You will develop your programming skills such that you are able to use Python to help you solve problems in maths and physics. The professional skills you will gain will help you with your study of physics, but also develop transferable skills which can be applied to a broader range of applications.

Module will run

Occurrence Teaching period
A Semester 1 2024-25

Module aims

Mathematics is fundamental to the study of Physics. This module will link the mathematical skills you gained before university to applications in physics. It will take your existing knowledge of calculus and algebra, deepening your understanding such that you develop the skills which will be needed for physics modules throughout your degree. You will also develop your programming skills such that you are able to use Python to help you solve problems in maths and physics. The professional skills you will gain will help you with your study of physics, but also develop transferable skills which can be applied to a broader range of applications.

Module learning outcomes

Mathematics:

  • Understand the difference between scalars and vectors and demonstrate an ability to use vectors to understand physical systems.

  • Understand the importance of complex numbers and be able to use them in a variety of applications for example the roots of polynomials.

  • Demonstrate an understanding of differentiation and integration in 1D and be able to use common methods to compute these.

  • Understand the meaning of partial derivatives and be able to calculate them in situations such as series expansions in multiple dimensions.

  • Understand the importance of first and second order differential equations and know how to solve them to analyse physical systems.

Computation:

  • Know how to construct a basic Python script and apply it to solve a physics problem.

Professional Skills:

  • Understand how the skills gained as a physicist provide preparation for employment in the future and communicate these ideas effectively.

  • Reflect upon your skills with a view to developing your transferable, practical and knowledge skills as you begin your development as a physicist.

  • Understand the concept of scientific enterprise, the diverse roles and sectors available to physicists and engage with constructive personal development activities.

  • Demonstrate a knowledge, understanding and applicability of basic statistics including probabilities, the binomial, Poisson and normal distributions, errors, and the standard error.

  • Be aware of scientific ethical issues.

  • Use computer software for numerical and graphing applications in physics.

Module content

Vectors: Scalars vs. Vectors, algebraic manipulation of vectors, methods of expressing vectors, scalar and vector products, vector equations of a plane and a line.

Sequences and Series: Arithmetic and geometric series, limits, hyperbolic functions, Maclaurin and Taylor expansions in 1D.

Complex Numbers: Representation in various forms, complex solutions of equations, the Argand diagram.

Differentiation: Recap of chain and product rules, higher order derivatives, partial derivatives, use of partial derivatives in series expansions in more than one variable.

Differential Equations: First order differential equations: separation of variable and integrating factor, homogeneous and non-homogeneous second order differential equations.

Integration: Standard integrals, integration by substitution, integration by parts in 1D. Applications in physics.

Computation: Introduction to Python: introducing variable, functions, conditions, loops, lists and arrays.

Professional Skills: Academic integrity, ethics, introductions to scientific communication, problem solving, study skills, career planning, disability disclosure, personal development, skills-gathering, employability, information retrieval, IT and Office applications, concepts in probability and statistics, experimental measurement techniques, plotting scientific data, recording data and analysing errors, use of the library and information retrieval.

Assessment

Task Length % of module mark
Closed/in-person Exam (Centrally scheduled)
Mathematical, Computational & Professional Skills 1		 2.5 hours 60
Essay/coursework
Computational Assignments		 N/A 15
Essay/coursework
Physics Practice Questions		 N/A 15
Essay/coursework
Professional Skills Assignments		 N/A 10

Special assessment rules

Other

Reassessment

Task Length % of module mark
Closed/in-person Exam (Centrally scheduled)
Mathematical, Computational & Professional Skills 1		 2.5 hours 60
Essay/coursework
Computational Assignment		 N/A 15
Essay/coursework
Professional Skills Assignments		 N/A 10

Module feedback

'Feedback’ at a university level can be understood as any part of the learning process which is designed to guide your progress through your degree programme. We aim to help you reflect on your own learning and help you feel more clear about your progress through clarifying what is expected of you in both formative and summative assessments.

A comprehensive guide to feedback and to forms of feedback is available in the Guide to Assessment Standards, Marking and Feedback. This can be found at:

https://www.york.ac.uk/students/studying/assessment-and-examination/guide-to-assessment/

The School of Physics, Engineering & Technology aims to provide some form of feedback on all formative and summative assessments that are carried out during the degree programme. In general, feedback on any written work/assignments undertaken will be sufficient so as to indicate the nature of the changes needed in order to improve the work. Students are provided with their examination results within 25 working days of the end of any given examination period. The School will also endeavour to return all coursework feedback within 25 working days of the submission deadline. The School would normally expect to adhere to the times given, however, it is possible that exceptional circumstances may delay feedback. The School will endeavour to keep such delays to a minimum. Please note that any marks released are subject to ratification by the Board of Examiners and Senate. Meetings at the start/end of each semester provide you with an opportunity to discuss and reflect with your supervisor on your overall performance to date.

Our policy on how you receive feedback for formative and summative purposes is contained in our Physics at York Taught Student Handbook.

Indicative reading

Stroud K A: Engineering Mathematics, 5th Ed 2001 (Palgrave)

James G: Modern Engineering Mathematics, 4th Ed 2010 (Pearson)

Mary L. Boas: Mathematical Methods in the Physical Sciences, Wiley

John M. Lannon & Laura J. Gurak: Technical Communication, Global Edition. 15th Ed 2021 (Pearson)


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.