Last modified: 11 Nov 2025 11:46
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 |
|---|---|---|---|
| Term | Second Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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Statistics has a crucial role to play in everyday life when data is involved, especially in the present era of digital information. It helps us make informed decisions, understand risks, and interpret information in various contexts. From personal finance and health choices to understanding news and planning daily activities, statistical concepts are constantly in operation play.
As a versatile field, statistics has applications across numerous professional areas. It involves collecting, analysing, interpreting, and presenting data in various forms to inform decision-making and problem-solving. From engineering to social sciences, statistics provides valuable insights and tools for many professions.
In this course, students will learn about (1) basic data handling, summarisation and visualisation – graphical displays, tabulation, cleaning data, and presentation; (2) introduction to probability distributions random sampling; (3) concepts of confidence intervals and hypothesis testing with simple examples; (4) relationships – correlation and regression.
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 15 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Duration: 1.5 hours |
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| 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 | 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 | Implement some hypothesis tests and construct corresponding confidence intervals |
| Procedural | Understand | Use RStudio to solve statistical problems. |
| Procedural | Understand | Understand elementary probability theory |
| Reflection | Evaluate | Write brief reports on analyses of data sets |
| Assessment Type | Summative | Weighting | 15 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Duration: 1 hour |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Factual | Analyse | Summarise data graphically and numerically |
| Procedural | Evaluate | Calculate probabilities in simple cases |
| Procedural | Understand | Implement some hypothesis tests and construct corresponding confidence intervals |
| Procedural | Understand | Understand elementary probability theory |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Understand | Use RStudio to solve statistical problems. |
| Procedural | Understand | Understand elementary probability theory |
| Procedural | Evaluate | Calculate probabilities in simple cases |
| Factual | Analyse | Summarise data graphically and numerically |
| Procedural | Understand | Implement some hypothesis tests and construct corresponding confidence intervals |
| Reflection | Evaluate | Write brief reports on analyses of data sets |
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