Last modified: 23 Jul 2024 11:16
The course emphasises the understanding and interpretation of data sets, discussing the key ideas of descriptive and inferential statistics in astronomy which can be adapted to other areas. It aims to explain how to summarise observational data graphically and numerically, to demonstrate the ideas behind probability theory, to introduce statistical inference, illustrated by examples of confidence intervals and hypothesis testing, and to show how such techniques are implemented on a computer.
| Study Type | Undergraduate | Level | 1 |
|---|---|---|---|
| Term | Second Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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Statistical analysis of experimental data is central to scientific methodology. It enables us to apply rational reasoning to measurements to obtain reliable and verifiable quantified knowledge and properties of nature. Probability theory is an effective tool for dealing with measurements that involve random numbers and more generally for approaching problems with incomplete knowledge. It guides how confident we can be in our understanding of the celestial objects and even the Universe as a whole, given limited observations. The predictions based on observational data are of a statistical nature and probability theory helps us discover new astronomical events and test astrophysical theories.
The course teaches students how to summarise data effectively and how to correctly interpret it in the astronomical text. However, the statistical concepts and methods are generic and can be applied to other scientific areas. Among the topics covered are sampling strategies, probability theory, confidence intervals and hypothesis tests. There are also computer practicals using the statistical programming language R. The mathematical context is emphasised, but students are not expected to have a high level of maths. Students taking this course will learn about basic data handling, summarisation and visualisation – graphical displays, tabulation, cleaning data, presentation; an introduction to probability distributions; random sampling; the concepts of confidence intervals and hypothesis testing; relationships – correlation and regression.
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 15 | |
|---|---|---|---|---|
| Assessment Weeks | 39 | Feedback Weeks | 39 | |
| Feedback |
Duration: 1 hour within 48 hours Feedback via MyAberdeen |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Factual | Analyse | Summarise astronomical data graphically and numerically. |
| Procedural | Apply | Implement some hypothesis tests and construct corresponding confidence intervals for astronomical statistical inference. |
| Procedural | Evaluate | Calculate probabilities for simple astronomical events. |
| Procedural | Understand | Understand elementary probability theory in astronomical context. |
| Assessment Type | Summative | Weighting | 70 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Factual | Analyse | Summarise astronomical data graphically and numerically. |
| Procedural | Apply | Implement some hypothesis tests and construct corresponding confidence intervals for astronomical statistical inference. |
| Procedural | Apply | Use the programming language R to solve statistical problems in astrophysics. |
| Procedural | Evaluate | Calculate probabilities for simple astronomical events. |
| Procedural | Understand | Understand elementary probability theory in astronomical context. |
| Reflection | Evaluate | Write brief reports on analyses of observational data sets. |
| Assessment Type | Summative | Weighting | 15 | |
|---|---|---|---|---|
| Assessment Weeks | 32 | Feedback Weeks | 32 | |
| Feedback |
Duration: 1.5. hours within 48 hours Feedback via MyAberdeen |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Factual | Analyse | Summarise astronomical data graphically and numerically. |
| Procedural | Apply | Implement some hypothesis tests and construct corresponding confidence intervals for astronomical statistical inference. |
| Procedural | Evaluate | Calculate probabilities for simple astronomical events. |
| Procedural | Understand | Understand elementary probability theory in astronomical context. |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Feedback via MyAberdeen |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
|
|
||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Factual | Analyse | Summarise astronomical data graphically and numerically. |
| Procedural | Evaluate | Calculate probabilities for simple astronomical events. |
| Procedural | Understand | Understand elementary probability theory in astronomical context. |
| Procedural | Apply | Implement some hypothesis tests and construct corresponding confidence intervals for astronomical statistical inference. |
| Procedural | Apply | Use the programming language R to solve statistical problems in astrophysics. |
| Reflection | Evaluate | Write brief reports on analyses of observational data sets. |
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