The everyday life of human beings is today summarized in a numbers – a world of data. From the food we eat, our health, clothing, transportation, and to technologies we are constantly exposed to, data remains the bedrock of our understanding of these facets of our living. However, making sense of these constantly emanating data – some of which are simple and some which are complex – analysis skills are fundamental.

Data analysis, interpretation, and presentation are essential skills every scientist is required to be successful. Often scientists struggle with the question of what type of data they should collect, how to collect the data, how to clean the data, how and what approaches to analyze the collected data, and how to interpret and make sense of the analyzed data. Understanding these issues and gaining mastery of them are crucial for achieving our overarching goals as scientists towards meaningfully contributing to societal growth and our science career.

This course takes participants through the journey of understanding the fundamental principles of data analysis and help participants to successfully navigate through their everyday data analysis needs and challenges. The course will be taught with practical illustration on three commonly used data analysis software – SPSS, Stata, and R, depending on the preference of each participant. Tutoring is participatory, with hands-on practical sessions that allow participants to implement the skills learned.

The course is suitable for postgraduate students, junior and senior researchers and principal investigators from any field of research.

Brief content:

• Day 1: Introduction, contexts, and overview of the scientific process
• Day 2: The data collection process and hands-on review of software
• Day 3: Data entry, cleaning and editing and principles of data analysis
• Day 4: Descriptive and analytic data analysis strategies
• Day 5: Group presentations and conclusions