Biostatistics module (GM51092)

You will have an introduction to statistical procedures for use with routine observational data using R studio. You will learn to have a supporting role in developing skills to understand statistical issues in clinical trials and to implement appropriately the analyses and reporting of results. You will acquire and demonstrate proficiency in statistical software, including Excel and R Studio for data analysis.

This module is delivered fully online, with discussion boards and interdisciplinary tutor support throughout.

What you will learn

In this module, you will

• Review Descriptive Statistics 
• Review Graphical Presentation 
• Think around Survey Design 
• Learn about Linear and Logistic Regression 
• Review Study Design Fundamentals 
• Learn about Advanced Statistical Methods 
• Apply knowledge to calculate Survival Analysis , Cox Proportional Hazards Models, Advanced Time-to-Event Models and Longitudinal Data Analysis

By the end of this module, you will be able to:

• Acquire and demonstrate knowledge of the fundamental principles of biostatistics in the context of global public health. 
• Critically reflect on the principles, theories, concepts, and practices of advanced statistical methods applied to global health data.
• Proficiently use and interpret key statistical concepts such as central tendency, variability, normal distribution, frequency, and probability within global public health datasets. 
• Select and apply appropriate statistical techniques to analyse global health data using descriptive, inferential, and advanced procedures. 
• Analyse clinical and public health intervention outcomes effectively and present results clearly, whilst adjusting, where appropriate, for biases and confounding in routine public health and epidemiological data

Assignments / assessments

Part 1: Case vignette-based essay (2,000-word equivalent) (50%)

Part 2:  There is a choice of undertaking only one of the following elements;

Part 2A: a practical data analysis task (1500 words) using R Studio/Excel to analyse a public health dataset, testing practical skills (50%).

• "Practical Data Analysis Assignment"  
  • Reflects the hands-on use of statistical software (R Studio/Excel) and analysis of a public health dataset. 
• "Applied Biostatistics Project"  
  • Emphasizes the application of biostatistics to real-world data, aligning with the module’s aims. 

OR 

PART 2B: a 1500-word critical review of a published study could assess theoretical understanding (50%). 

• "Critical Study Review"  
  • Highlights the critical evaluation of a published public health study’s statistical methods. 
• "Statistical Literature Analysis"  
  • Focuses on analyzing statistical approaches in global health literature

This module does not have a final exam

Teaching methods / timetable

• Pre-recorded lectures
• Discussion boards for weekly peer and tutor interaction
• On-demand online resources and tutor support

This module is delivered fully online