PH30116: Data analysis and research methods for observational astronomy
[Page last updated: 21 April 2022]
Academic Year: | 2022/3 |
Owning Department/School: | Department of Physics |
Credits: | 6 [equivalent to 12 CATS credits] |
Notional Study Hours: | 120 |
Level: | Honours (FHEQ level 6) |
Period: |
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Assessment Summary: | CW 100% |
Assessment Detail: |
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Supplementary Assessment: |
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Requisites: | Before taking this module you must ( take PH10007 OR take MA10207 ) AND ( take PH10102 OR take PH20018 ) AND take AT LEAST 1 MODULE FROM {PH20016, PH20076, PH20106, PH20114} AND ( take PH20107 OR take MA20216 ) |
Learning Outcomes: | After taking this unit, the student should be able to:
* plan and evaluate astronomical observations based on their understanding of instrumentation; * apply data reduction techniques; * apply basic modelling techniques; * apply and interpret statistical tests; * perform literature searches specific to astrophysics; * present research result clearly in writing; * critically assess aspects of astronomical literature; * work independently on a research project; * solve problems independently and in a group. |
Aims: | The aim of this unit is to introduce students to data analysis and research methods in observational astronomy. They will familiarize themselves with the areas of instrumentation, data analysis, modelling, statistical analysis, observation planning/proposal writing and presentation of scientific results. Students will learn to work independently on data analysis tasks and to assess their work and those of others critically. |
Skills: | Written Communication T/F A, Numeracy T/F A, Data Acquisition, Handling, and Analysis T/F A, Information Technology T/F A, Problem Solving T/F A. |
Content: | Instrumentation: Astronomical instrumentation & detectors; current facilities in astronomy; choosing the appropriate setup for a science question.
Data analysis: Astronomical data reduction (photometry); optical data reduction (bias, flatfielding, calibration); error estimation for astronomical data; implementation of techniques in Python. Modelling: Introduction to modelling; fitting techniques (least squares, ML); model comparison); implementation of modelling techniques in Python. Interpretation: Selection effects; combining datasets. Proposals: Observation planning; proposal writing. Presentation: Astronomical literature search and standards; publication processes. |
Programme availability: |
PH30116 is Optional on the following programmes:Department of Physics
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Notes:
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