Many important real-world problems -- whether in research, business, government, or even everyday life -- must be solved in uncontrolled settings under conditions of high uncertainty. The purpose of this module is to prepare you to apply scientific thinking to such problems.

We will begin by ensuring that you have a clear understanding of the nature and purpose of science and the application of the classical scientific method to simple problems. You will then learn how to approach the challenges of well-controlled laboratory research studies, such as framing research questions, controlling quality and bias, and designing explicit and definitive tests of competing hypotheses or models.

With this foundation in place, we will then consider more complex problems, beginning with advanced laboratory research. We will then move on to the real world where experimental control is limited and uncertainty is high, but problems must nonetheless be solved, often with great urgency. You will learn how to develop solutions to real-world problems that are as relevant and robust as possible, and how to manage the intersection of science with other sectors (e.g., media, government).

The module will draw on a wide range of problems from biosciences and beyond, with key concepts reinforced through assignments requiring you to develop and critique research reports, funding proposals, and policy recommendations, both individually and in groups.

The module will require extensive active engagement, both inside and outside of the classroom. It is not recommended for those seeking to undertake passive or asynchronous learning.

After completing this module you will be able to:

understand the nature, purpose and limitations of modern science and the benefits and challenges of science in the real world
	critically review laboratory research papers and grant proposals
	assess the relevance of lab science to real world problems
	make inferences without controlled experiments
	understand the disconnect between science, popular opinion, and policy
	understand current best practice for solving urgent, complex real-world problems