FY540: Experimental and computational physics and statistical data analysis
Study Board of Science
Teaching language: Danish, but English if international students are enrolled
EKA: N500032112, N500032122, N500032102
Assessment: Second examiner: None, Second examiner: Internal
Grading: Pass/Fail, 7-point grading scale
Offered in: Odense
Offered in: Autumn
Level: Bachelor
STADS ID (UVA): N500032101
ECTS value: 10
Date of Approval: 27-03-2019
Duration: 1 semester
Version: Archive
Comment
Entry requirements
Academic preconditions
. Students taking the course are expected to:
- Have knowledge of basic mechanics, electromagnetism and thermodynamics.
- Have knowledge of basic calculus including ordinary differential equations, partial derivatives and basic concepts in probability theory.
- Have knowledge of computational tools such as MATLAB
Course introduction
The aim of the course is to enable students to (1) plan and perform experiments in physics, (2) implement and simulate mathematical models, (3) conduct statistical analysis of the acquired data and compare with relevant theory, and (4) obtain a rudimentary understanding of how science, including physics, impact societ through innovations.
The course builds on the knowledge acquired in physics courses on the first year of the curriculum. The course provides a basis for later courses in experimental, computational, and statistical physics, and for doing individual projects or participating in research projects.
In relation to the competence profile of the degree it is the explicit focus of the course to:
- Be able to investigate physical phenomena by experiments
- Be able to analyse experimental problems and apply relevant analysis tools and concepts.
- Formulate mathematical models of physical systems
- Basic numerical calculus
- Implement and perform simulations of models.
- Statistics and probability theory
- Apply statistical methods to analyse data
- Data analysis and modelling to investigate innovation impact
Expected learning outcome
The learning objective of the course is that the student demonstrates the ability to:
- Describe the design and construction of experiments in the course.
- Describe the underlying theory of experiments in the course.
- Perform derivations of theoretical models of relevance for the experiments in the course.
- Perform experiments in the laboratory and assess the suitability of own results with respect to data analysis.
- Implement models on the computer and simulate them.
- Perform a quantitative analysis of data including the use of computational and statistical methods where relevant.
- Compare data and theoretical models.
- Account for experiments and results in the form of written reports.
- Understand theories for the origins and impact of innovations
Content
The course contains the following topics in probability theory and data analysis:
- Interpretation of probability: Bayesian and frequentist.
- Discrete and continuous probability distributions.
- Central limit theorem
- Parameter estimation
- Hypothesis testing
- Model selection
The following experimental topics are contained in the course:
- Surface tension and wetting.
- Brownian motion.
The course contains computational topics such as
- Numerical analysis
- Generation of random numbers
- Numerical solution of ODEs and PDEs
- Integration
- Data analysis, modelling and simulation of a simple model for origins and impact of innovations
Laboratory experiments and simulations are performed in groups of 2-3 students. As an introduction to the exercises, the central concepts and methods are introduced.
Literature
Examination regulations
Prerequisites for participating in the exam b)
Timing
Autumn
Tests
Solving of mandatory exercises, reports from laboratory experiments / simulation projects.
EKA
N500032112
Assessment
Second examiner: None
Grading
Pass/Fail
Identification
Full name and SDU username
Language
Normally, the same as teaching language
Examination aids
To be announced during the course
ECTS value
0
Additional information
The prerequisite examination is a prerequisite for participation in exam element a).
Prerequisites for participating in the exam a)
Timing
Autumn
Tests
Attendance at laboratory exercises
EKA
N500032122
Assessment
Second examiner: None
Grading
Pass/Fail
Identification
Full name and SDU username
Language
Normally, the same as teaching language
Examination aids
To be announced during the course
ECTS value
0
Additional information
The prerequisite examination is a prerequisite for participation in exam element a).
Exam element a)
Timing
January
Prerequisites
| Type | Prerequisite name | Prerequisite course |
|---|---|---|
| Examination part | Prerequisites for participating in the exam a) | N500032101, FY540: Experimental and computational physics and statistical data analysis |
| Examination part | Prerequisites for participating in the exam b) | N500032101, FY540: Experimental and computational physics and statistical data analysis |
Tests
Individual oral examination
EKA
N500032102
Assessment
Second examiner: Internal
Grading
7-point grading scale
Identification
Full name and SDU username
Language
Normally, the same as teaching language
Examination aids
To be announced during the course
ECTS value
10
Additional information
The individual oral examination is based on an assessment of the whole exam that also includes:
- Reports on the laboratory
- Computational projects
- Home work.
The examination form for re-examination may be different from the exam form at the regular exam.
Indicative number of lessons
Teaching Method
At the faculty of science, teaching is organized after the three-phase model ie. intro, training and study phase.
In the Intro phase an introduction is given to the principles behind the experimental and statistical work.
In the Skills training phase exercises are solved and the laboratory/computational work is completed on the basis of work done during the Intro phase.
In the Study phase, individual preparations are done for the Skills training phase and after the lab exercises data analysis and writing of reports is done.
Activities during the study phase:
- Study of textbook
- Reading of scientific papes.
- Problem solving
- Preparation for the experimental work
- Analysis of experimental data.
- Writing of reports
- Preparation for the oral exam
Teacher responsible
Additional teachers
| Name | Department | City | |
|---|---|---|---|
| Michael Andersen Lomholt | mlomholt@memphys.sdu.dk | ||
| Steen Rasmussen | steen@sdu.dk |