Application of statistical methods for interpreting large datasets.
About this course
Statistical Analysis introduces the mathematical tools needed to make sense of large, complex datasets in a security context. You will learn how to move from raw numbers to actionable insights, using methods that are standard in the industry for threat detection and risk assessment.
The course covers descriptive statistics, probability distributions, hypothesis testing, and regression analysis. You will work with real-world datasets to identify patterns, measure variability, and test assumptions about security events. The focus is on practical application, so you will spend a significant portion of the term using statistical software to clean, analyse, and visualise data.
Who takes this course
Credits: 3 · Hours: 45
Prerequisites
Learning outcomes
- Apply descriptive and inferential statistical methods to cybersecurity data
- Interpret statistical results to identify security trends and anomalies
- Design experiments and surveys to evaluate security controls
- Communicate statistical findings to technical and non-technical audiences
Evaluation
| Component | Weight (%) |
| Midterm exam | 30 |
| Data analysis project | 40 |
| Final exam | 30 |