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Statistics are fundamental for understanding quantitative data collected about the health of the public.
In this module you will learn basic concepts and skills for understanding and conducting statistical analyses commonly used in public health practice.
It will provide you with a grounding in key concepts, namely types of variables, inference, statistical methods for continuous and categorical variables (variability of single mean, comparison of two means, t-test, analysis of variance; variability of single proportion, comparisons of two and more proportions, chi-square test, Mantel-Haenszel test), linear regression, and logistic regression.
You will also have an introduction to statistical computing using Stata software.
Your online pre-recorded lectures will be complemented by computer practical sessions so that you can consolidate your knowledge and apply it in a variety of contexts relevant to public health.
Teaching and practical examples will include context-specific public health problems in high-, middle-, and low-income countries. You will also learn to interpret and present statistics for non-technical audiences, such as policymakers and the public. Finally, you will critically examine rising mistrust of statistics among the public, including the reasons for it and ways to improve trust, from the perspectives of citizens.
Aims of the module
The aim of the module is to introduce students to key statistical concepts and their application and interpretation in public health research and practice. This module will give students a grounding in one of the core disciplines of public health which will underpin learning through the MPH programme.