Experimental Design and Statistical Analysis Experimental design is one of the most important parts of doing science, but it is difficult to do well. How do you randomize mice? How many replicate petri plates should be inoculated? If I am measuring temperature in a forest, where do I put the thermometer? In this course students will design experiments across the sub-areas of biology. We will run student designed experiments, and then learn ways to analyze the data, and communicate the results. Students planning to do independent research are encouraged to take this course. (BIOL 0140 or BIOL 0145).

Principles of Epidemiology This course will introduce students to the theory and practice of epidemiology.  Students will learn major concepts including study design, measures of effect, and causal inference. We will explore the causes of modern diseases with a focus on how epidemiology can be used to understand causation of disease. We will also explore the historical and current contributions of epidemiology within the field of public health. The course will introduce areas of specialization including infectious and non-infectious diseases, environmental epidemiology, and social and community epidemiology. Students will learn data analysis skills applicable to research in public health and other quantitative sciences. Students will utilize skills from class to investigate an epidemiological issue using real world data. Students will also lead discussions on how epidemiology is used to investigate the determinants of disease. Students will leave the course with understanding of key epidemiological concepts, and the ability to convey those ideas to a lay audience in written and oral formats.

Ecology and Evolution In this introduction to ecology and evolutionary biology we will cover the topics of interspecific interactions (competition, predation, mutualism), demography and life-history patterns, succession and disturbance in natural communities, species diversity, stability and complexity, causes of evolutionary change, speciation, phylogenetic reconstruction, and population genetics.   The laboratory component will examine lecture topics in detail (such as measuring the evolutionary response of bacteria, adaptations of stream invertebrates to life in moving water, invasive species and their patterns of spread).  We will emphasize experimental design, data collection in the field and in the laboratory, data analysis, and writing skills. This course is not open to seniors and second semester juniors in the Fall.

Planetary Health Human health depends on planetary conditions and resources, as well as functioning ecosystems. Climate change, biodiversity loss, scarcity of land and freshwater, pollution and other threats are degrading these systems with profound implications for human health and wellbeing. Using an interdisciplinary approach, we will investigate the driving forces of human health and wellness in the Anthropocene with an eye on the role of ecology, evolution, planetary change, and the interconnected systems of our planet. Beyond assessing the fundamental biophysical forces acting on human health, we will additionally consider the societal values and ethical frameworks that are inherent to these issues.

Sam Byrne

Reviews and ratings for Sam Byrne at Middlebury College.Sam Byrne teaches Biostatistics, Principles of Epidemiology, Ecology and Evolution and more.  Explore top rated instructors and find the best for you.Is Sam Byrne good ? Find out on MiddCourses.

The actual course material is not heavy and easy to understand, especially for those who have background knowledge from AP Environmental Science. The hardest/most time-consuming part are the lab assignments. I would say that this is a good intro bio class for those wanting to see what science class/lab combo looks like. Despite the course material being repetitive from high school APES, Prof. Sam is AMAZING and the lab professors (Dash and Nurock) are also very nice and chill. Professor Sam definitely made the course worth taking, would 100% take a class with him again. 

Sam Byrne is such an awesome professor. He was super effective in teaching this course and presented really interesting case studies. The class was a little quiet at times which made the discussions difficult, however he was great at making sure we all got what we needed out of each class. 

Labs involved being taught R, while the lecture was more conceptual statistics. There was one low stakes coding exam before the final but overall there were not big exams in the course. The independent group project towards the end was also fun to apply what we learned. 