Last modified: 31 Jul 2023 11:19
This is a statistics course open to all first and second year students. It is a useful course for students whose degree subject involves some amount of statistical analysis. The course teaches students how to summarise data effectively and how to correctly interpret it. Among the topics covered are sampling strategies, probability theory, confidence intervals and hypothesis tests. There are also weekly computer practicals using the statistics software RStudio. The mathematical context is emphasised but students are not expected to have a high level of maths.
| Study Type | Undergraduate | Level | 1 |
|---|---|---|---|
| Session | Second Sub Session | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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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 with simple examples. Relationships – correlation and regression.
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 70 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Factual | Analyse | Summarise data graphically and numerically |
| Procedural | Evaluate | Calculate probabilities in simple cases |
| Procedural | Understand | Understand elementary probability theory |
| Procedural | Understand | Use RStudio to solve statistical problems. |
| Procedural | Understand | Implement some hypothesis tests and construct corresponding confidence intervals |
| Reflection | Evaluate | Write brief reports on analyses of data sets |
| Assessment Type | Summative | Weighting | 15 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Factual | Analyse | Summarise data graphically and numerically |
| Procedural | Evaluate | Calculate probabilities in simple cases |
| Procedural | Understand | Understand elementary probability theory |
| Procedural | Understand | Implement some hypothesis tests and construct corresponding confidence intervals |
| Assessment Type | Summative | Weighting | 15 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Factual | Analyse | Summarise data graphically and numerically |
| Procedural | Evaluate | Calculate probabilities in simple cases |
| Procedural | Understand | Understand elementary probability theory |
| Procedural | Understand | Implement some hypothesis tests and construct corresponding confidence intervals |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
|
|
||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Factual | Analyse | Summarise data graphically and numerically |
| Procedural | Evaluate | Calculate probabilities in simple cases |
| Procedural | Understand | Understand elementary probability theory |
| Procedural | Understand | Implement some hypothesis tests and construct corresponding confidence intervals |
| Procedural | Understand | Use RStudio to solve statistical problems. |
| Reflection | Evaluate | Write brief reports on analyses of data sets |
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