Outline:

This module aims to provide students with a foundation in practical physics, computing and data analysis. Students will conduct experiments and/or observations and record, analyse and report on their results. Students will gain practical experience in mapping physics problems onto a computational framework, and will use computers to model, visualize and solve physical problems using Python. In parallel, students will learn data analysis and statistical techniques, and apply them to evaluate data and discover meaningful information.

Aims:

All practical and computing modules within the Department contribute to a continuing development of students’ scientific, technical and transferable skills, extending throughout their degree programmes. Collectively, these modules have the overall aim of equipping the student with those practical skills which employers expect to find in physics-related graduates, whether they are employed in scientific research or development, or in a wider context. PHAS0007 is the first practical module encountered by students making the transition from school to University level studies. As such, it aims to take the first steps in the process of training and developing physics practical skills.

Teaching and Learning Methodology:

In the laboratory sessions, both in the introductory experimental skills part and the main series of experiments and observations, students work by following guidance scripts. Great emphasis is placed on the formation of good habits in the keeping of a notebook for which students are given detailed advice. Demonstrators not only help students understand experiments and observations and overcome difficulties as they arise, but also inspect students’ notebooks to provide formative feedback to help develop good practices.

In the computing element, practical programming sessions teach essential computing skills using Python, including computational treatment of data and creating computational models of physical systems.

The data analysis and statistics lectures will introduce basic principles of data analysis and statistics, as well as multiple practical examples that you will use in both the computing and laboratory sessions.