Course Curriculum

Doing statistical analysis doesn't need to be painful. This course will take you through the most important and commonly used statistical tools and provide you with an understanding of the "scientific method" that underpins data analysis.

  • 01

    Describing and analysing data

    • Descriptive statistics and data visualization

    • Inferential statistics and hypothesis testing

    • Non-parametric tests

    • Missing data

  • 02

    Research methods

    • Research methods - intro

    • An overview of quantitative and qualitative methods

    • Case control vs. cohort studies

    • Randomised controlled trials and confounding

  • 03

    Introduction to R

    • Why use R

    • R example analysis

  • 04

    Additional resources

    • Tutors' quick guide to statistics

  • 05

    Discussion and feedback

    • Discussion

    • Feedback

Once you've completed the course you'll have a good understanding of the various types of data, how to create and use a data dictionary, how to best describe and visualize your data, and how to use the most common statistical tests. You'll also learn about the assumptions that get made when applying statistical tests and when to use "non-parametric" tests.

Instructor

Instructor Bio:

Dr Greg Martin is a medical doctor with a Masters in Public Health and an MBA degree. His professional experience includes working as the Head of Science and Research at the World Cancer Research Fund and the Director of Elimination of Mother to Child Transmission at the Clinton Health Access Initiative. He is also the founder and Editor-in-Chief of the peer-reviewed journal Globalization and Health. 

Greg Martin