This course, "Uncertainty and Research," offered by Johns Hopkins University, delves into the fundamentals of scientific research with a focus on reducing uncertainty through Bayesian methods. The course is designed for learners new to research fields or those seeking to enhance their research skills in any professional or personal capacity. The curriculum is presented at an introductory level, enabling participants to formulate research hypotheses and develop scientific research plans by the course's conclusion.
The course begins by exploring the scientific landscape and the various types of research, their locations, and their significance. It then delves into scientific inquiry, distinguishing between scientific and non-scientific explanations and methods of inquiry. The language of scientific investigation, the steps of the research process, and theories and hypotheses are also covered. Moreover, the essentials of probability, Bayes' Rule, and uncertainty quantification in the research process receive thorough attention. The course culminates by illustrating how research serves as an exercise in uncertainty quantification and Bayesian hypothesis testing.
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This comprehensive course is structured into five modules, covering the research landscape, scientific inquiry, the scientific method, uncertainty and probability, and research as an exercise in uncertainty quantification (UQ).
The first module, "Introduction to the Research Landscape," provides an overview of the scientific landscape, the motivations behind research, the importance of scientific research, and the spectrum of research activities. Learners gain insight into the locations where research is conducted and the personal goals associated with research endeavors.
The second module, "Scientific Inquiry," delves into what constitutes a scientific explanation, distinguishing between scientific and non-scientific explanations, methods of inquiry, and the scientific method. It also explores the concepts of science, pseudoscience, and identifying pseudoscience.
The third module, "Scientific Method & the Research Process," focuses on the language of scientific investigation, theories and hypotheses, theory-driven vs. data-driven research, and research program development. It illuminates the steps of the research process and how it is inherently scientific.
The fourth module, "Uncertainty & Probability," covers the essentials of set theory, probability, the law of total probability, and Bayes' Rule. Learners are introduced to different types of uncertainties and engage in Bayes' Rule problems to enhance their understanding of uncertainty quantification.
The fifth module, "Research as an Exercise in Uncertainty Quantification (UQ)," delves into uncertainty quantification and the scientific method, Bayesian hypothesis testing, and testing multiple hypotheses. It includes a Bayesian hypothesis testing lab quiz and exemplifies how research serves as an exercise in uncertainty quantification.
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