Advances in digital technology are creating new ways to quantify biological processes and properties, from the scale of molecules to ecosystems. The life scientist of the 21st century needs to understand how to collect, manage, synthesise, and communicate this information within a reproducible workflow in order to make robust inferences about the natural world. This intensive unit of study will introduce you to key concepts and tools across three modules: digital project and data management, evidence synthesis and meta-analysis, and scientific coding using R. The focus is on active learning, discussion, and problem-solving across intensive workshop-based practicals, rather than the traditional lecture format. By completing this unit you will further understand the practical realities of scientific inquiry. To that end, you will develop a flexible skillet for conducting reproducible and open research to ensure the results of your work are maximally beneficial to both your future self and the broader community. Knowledge of how to work with data through the entire pipeline -from sampling to synthesis-will be useful wherever it is encountered in your education, career, and life.
Unit details and rules
|Life and Environmental Sciences Academic Operations
|144 credit points of units of study including a minimum of 24 credit points at the 3000- or 4000-level and 18 credit points of 3000- or 4000-level units from Science Table A or 1
Completion of units in quantitative research methods, mathematics or statistical analysis at least at 1000-level
|Available to study abroad and exchange students
|Thomas White, firstname.lastname@example.org