Undergraduate Course: Programming and Data Analysis (PHYS08049)
Course Outline
| School | School of Physics and Astronomy |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This course provides an introduction to computer programming and data analysis. It serves as a preparation for further study in some physics-related degree programmes, and as a stand-alone course for students of other disciplines, including mathematics, chemistry, geosciences, computer science and engineering. The course consists of laboratory sessions and workshops to develop understanding, familiarity and fluency. |
| Course description |
Scientific Programming
- Introduction to python programming, basics of Linux, executing programmes
- Data types, variables and operators
- Command line and file input and output
- Conditional statements, loops and lists
- Importing and using python modules, mathematical functions, simple graphs
- Introduction to functions
- Reusable code, finding and fixing bugs
Data Analysis
- Uncertainty, accuracy and precision
- Mean value; standard deviation; error on the mean
- Using a spreadsheet for data analysis
- Combining uncertainties
- Graphs and graph plotting
- Least squares methods
- Application to a real-world problem
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | Students MUST NOT also be taking
Practical Physics (PHYS08048)
|
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2017/18, Available to all students (SV1)
|
Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Supervised Practical/Workshop/Studio Hours 33,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
65 )
|
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
60% Programming/Computing Skills
40% Data Analysis |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Present a record of a computation or data analysis in an appropriate, clear and logical written form (e.g. fully documented computer code or annotated spreadsheet), augmented with figures and graphs where appropriate
- Assess whether an output from data analysis or a computer program is physically reasonable
- Locate and use additional sources of information (to include discussion with peers where appropriate) to resolve problems that arise in the computational physics laboratories
- Explain the importance of reproducibility of scientific work, and the role that quantitative statements of confidence in results play in achieving this
- Take responsibility for learning by attending laboratory sessions and workshops, and completing coursework
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | PDA |
Contacts
| Course organiser | Prof Malcolm Mcmahon
Tel: (0131 6)50 5956
Email: |
Course secretary | Mrs Bonnie Macmillan
Tel: (0131 6)50 7218
Email: |
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