Module Aims:

This core module aims to provide students with the necessary knowledge and biostatistical skills to be able to interpret and conduct basic statistical analyses of population health data. Students may choose to take this, or Statistics for HDS

Module Learning Outcomes:

By the end of the module, students should be able to:

1. Understand sampling variation in the context of population health studies
2. Use R to manipulate data and to apply and interpret the output of commonly used statistical procedures
3. Select, perform and interpret appropriate descriptive analyses of population health data
4. Select, apply and interpret common regression models for the statistical analysis of population health data
5. Perform standard sample size and power calculations

 

Pre-requisites:

Fluent numeracy and a good understanding of elementary algebra (e.g. rearranging equations, graphical interpretation of a linear equation in two variables, simultaneous linear equations when the solution is unique, quadratic equations), logarithms (and performing operations on logarithmic scale), summation notation (∑), and probability (including performing simple probability operations). Familiarity with scientific notation, and with performing automated calculations (e.g. in excel, R, or equivalent).

 

Teaching Strategy:

The module will be delivered using a combination of lectures, class discussion, small-group exercises, and computer practical. Some reading may be required prior to some sessions.

Assessment:

A timed open book assessment approximately 1 week after the end of the module, consisting of a data analysis task and associated report.

Module Length: 8 days over 4 weeks