The Basic Statistics for Public Health & Policy module is a core module designed to introduce students to the basic concepts and methods of statistics, as applied in the various disciplines of public health.

Intended learning outcomes

Upon successful completion of the module, a student will be able to:

• Describe the role of statistical methods in public health research.
• Report results clearly and concisely by making appropriate displays, summaries and tables of data.
• Explain the problem of sampling variation, and the role of statistical methods in quantifying this.
• Recognise the importance of sample size calculations.
• Select an appropriate statistical method for the analysis of different types of data.
• Interpret the results of statistical analyses reported in the health literature.
• Employ simple statistical analyses using statistical computing software.

Session Content

The module is expected to cover the following topics:

• Describing data: tables and graphs; proportions; measures of central tendency (mean, median), and spread (range, standard deviation); differences and ratios.
• Sampling variability: confidence intervals and p-values, especially for means and proportions, and for differences in means and proportions.
• Sample size calculations.
• Simple linear regression analysis and correlation coefficients and an introduction to multivariable analysis.
• Interpreting statistics commonly reported in the health literature.
• Statistical analyses by computer.

Mode of delivery

This module is delivered predominantly face-to-face. Where specific teaching methods (lectures, seminars, discussion groups) are noted in this module specification these will be delivered by predominantly face-to-face sessions. There will be a combination of live and interactive activities (synchronous learning) as well as self-directed study (asynchronous learning).

Assessment

The assessment for this module has been designed to measure student learning against the module intended learning outcomes (ILOs) as listed above. Formative assessment methods may be used to measure students’ progress. The grade for summative assessment(s) only will go towards the overall award GPA.

There will be a mid-term formative assessment and the summative assessment for this module will be a data analysis exercise to be submitted in week 0 of Term 2.

Credits

• CATS: 10
• ECTS: 5

Module specification

For full information regarding this module please see the module specification.

Please note: information based on the 2025-26 module specification subject to change for 2026-27 entry.