Methodological Advances
Code: 104866 ECTS Credits: 6| Degree | Type | Year | Semester |
|---|---|---|---|
| 2503852 Applied Statistics | OT | 4 | 2 |
Contact
- Name:
- Manuel Carlos Delfino Reznicek
- Email:
- manuel.delfino@uab.cat
Use of Languages
- Principal working language:
- spanish (spa)
- Some groups entirely in English:
- No
- Some groups entirely in Catalan:
- No
- Some groups entirely in Spanish:
- No
Teachers
- Marķa del Pilar Casado Lechuga
- Oscar Blanch Bigas
Prerequisites
There are no formal prerequisites. It is recommended to have completed the core subjects of the first three courses of the Degree.
Objectives and Contextualisation
Humanity's view of the Universe changed radically in the 20th Century. The evolution of detection techniques has increased the number of viewable objects in the sky from a few hundred to many billion. In addition, objects can be viewed through electromagnetic radiation over a wide range of wavelengths, from radio and infrared to the visible band and up to x-rays. Elementary particle physics techniques have been adapted to allow observations of higher energy photons up to Very High Energy gamma rays. These techniques also allow, for the first time, observation of the sky through non-electromagnetic messengers, namely charged particles ("cosmic rays") and, very recently, neutrinos. Finally, very large and precise laser interferometers have recently observed gravitational waves, which bring yet another way to observe objects in the sky.
All of these ways of observing the Universe are producing huge amounts of data that need to be cleaned, calibrated, analyzed and compared to theoretical predictions. This requires the use of large computer clusters optimized for data-intensive applications as well as supercomputers for simulations combined with sophisticated statistical analyses and uncertainty estimations. Big Data and Artificial Intelligence techniques are increasingly being applied in the field. The objective of the course is to explore these techniques in the context of the Degree.
Competences
- Design a statistical or operational research study to solve a real problem.
- Select statistical models or techniques for application in studies and real-world problems, and know the tools for validating them.
- Students must be capable of applying their knowledge to their work or vocation in a professional way and they should have building arguments and problem resolution skills within their area of study.
- Students must be capable of collecting and interpreting relevant data (usually within their area of study) in order to make statements that reflect social, scientific or ethical relevant issues.
- Students must be capable of communicating information, ideas, problems and solutions to both specialised and non-specialised audiences.
- Summarise and discover behaviour patterns in data exploration.
Learning Outcomes
- Establish the experimental hypotheses of modelling.
- Identify the response, explanatory and control variables.
- Plan studies based on time series.
- Recognise the need to use models of stochastic processes.
- Students must be capable of applying their knowledge to their work or vocation in a professional way and they should have building arguments and problem resolution skills within their area of study.
- Students must be capable of collecting and interpreting relevant data (usually within their area of study) in order to make statements that reflect social, scientific or ethical relevant issues.
- Students must be capable of communicating information, ideas, problems and solutions to both specialised and non-specialised audiences.
- Use summary graphs for multivariate data and temporal evolution data.
Content
- Observing the sky: Physics, models and simulations, observations and instruments.
- Case Study: Optical Sky Surveys: Measuring the expansion of the Universe
- Case Study: Imaging Atmospheric Cherenkov telescopes: Measuring the non-thermal Universe
- Case Study: The violent Universe: Neutrino astronomy with huge volumes of instrumented ice or water
- Case Study: The violent Universe: Detecting gravitational waves with laser interferometers
Methodology
The course will be organized in 5 modules of 2-3 week duration. The introduction to each module will be given in Lectures. Afterwards the students will work on understanding a number of Case Studies, taking a critical look at existing solutions and proposing improvements.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Activities
| Title | Hours | ECTS | Learning Outcomes |
|---|---|---|---|
| Type: Directed | |||
| Lectures | 15 | 0.6 | 1, 8, 2, 3, 6, 4 |
| Type: Supervised | |||
| Case Studies | 25 | 1 | 1, 8, 2, 3, 7, 5, 6, 4 |
| Type: Autonomous | |||
| Development of solutions and programs | 50 | 2 | 1, 8, 2, 3, 7, 5, 6, 4 |
| Study | 45 | 1.8 | 1, 8, 2, 3, 4 |
| Tutorials with professors | 5 | 0.2 | 1, 8, 2, 3, 7, 5, 6, 4 |
Assessment
The more theoretical aspects will be evaluated through a Continuous Evaluation Assessment of 2 hour duration. The more practical aspects will be evaluated through Presentations and Participation in Debates, each of about 2 hour duration.
Assessment Activities
| Title | Weighting | Hours | ECTS | Learning Outcomes |
|---|---|---|---|---|
| Continuous Assessment Tests | 14% | 2 | 0.08 | 1, 2, 7, 4 |
| Presentations and participation in debates | 86% | 8 | 0.32 | 1, 8, 2, 3, 7, 5, 6, 4 |
Bibliography
Física nuclear y de partículas (3a edición)
Full Text Access:
Unebook Intercambio Científico (UAB) 2020 http://web.b.ebscohost.com/pfi/ExternalLinkOut/PubFinderLinkOut?sid=857a256b-c942-49c2-b16a-ae47c0e48468@pdc-v-sessmgr03&vid=3&Url=https%3a%2f%2flogin.are.uab.cat%2flogin%3furl%3dhttps%3a%2f%2flectura.unebook.es%2fviewer%2f9788437097718&Kbid=edp10590268&PackageId=3880399&LinkedFrom=PublicationDetail
Author:
Ferrer Soria, Antonio
ISBN:
978-84-370-9645-2
978-84-370-9771-8
Publisher Information:
Publicaciones de la Universidad de Valencia
Resource Type:
Book
Subjects:
Science
Particle Physics Reference Library: Volume 2: Detectors for Particles and Radiation
Full Text Access:
DOAB Directory of Open Access Books 2020 http://web.b.ebscohost.com/pfi/ExternalLinkOut/PubFinderLinkOut?sid=857a256b-c942-49c2-b16a-ae47c0e48468@pdc-v-sessmgr03&vid=5&Url=https%3a%2f%2flibrary.oapen.org%2fbitstream%2f20.500.12657%2f41753%2f1%2f2020_Book_ParticlePhysicsReferenceLibrar.pdf&Kbid=edp26617004&PackageId=5937&LinkedFrom=PublicationDetail
Springer Physics and Astronomy eBooks 2020 English/International 2020 http://web.b.ebscohost.com/pfi/ExternalLinkOut/PubFinderLinkOut?sid=857a256b-c942-49c2-b16a-ae47c0e48468@pdc-v-sessmgr03&vid=5&Url=https%3a%2f%2flogin.are.uab.cat%2flogin%3furl%3dhttps%3a%2f%2flink.springer.com%2f10.1007%2f978-3-030-35318-6&Kbid=edp26617004&PackageId=3488474&LinkedFrom=PublicationDetail
SpringerOpen Books 2020 http://web.b.ebscohost.com/pfi/ExternalLinkOut/PubFinderLinkOut?sid=857a256b-c942-49c2-b16a-ae47c0e48468@pdc-v-sessmgr03&vid=5&Url=https%3a%2f%2flogin.are.uab.cat%2flogin%3furl%3dhttps%3a%2f%2flink.springer.com%2f10.1007%2f978-3-030-35318-6&Kbid=edp26617004&PackageId=2884047&LinkedFrom=PublicationDetail
Author:
Fabjan
Niko, editor
ISBN:
978-3-030-35317-9
978-3-030-35318-6
Publisher Information:
Springer International Publishing
Resource Type:
Book
Subjects:
English Language
Software
Any type of spreadsheet (LibreOffice Calc, Google Sheets, Microsoft Excel, etc.)
Online pages that generate graphics (desmos.com, geogebra, etc.)
python
Jupyter notebooks