Required of Post-Doctoral and Training Grant Fellows. The grading basis for this course is Satisfactory/Unsatisfactory.
Agriculture, Food, and the Environment
To enroll in a Directed Study course, please complete and submit the Directed Study Course Proposal Form (available at: http://nutrition.tufts.edu/students/registrar/forms) by the semester's Add Deadline to the Registrar's Office so the Directed Study course may be manually added to your schedule in SIS.
Agriculture and food industries are a subject of growing interest in terms of their resource requirements, ecological impacts, and sustainability. This course will provide a foundation in some of the methods of modeling and analysis used to study food systems. We will address several types of approaches, generally building in complexity, starting with net balances of production and consumption and continuing through modeling food production capacity, foodshed analyses, life cycle assessment, and system dynamics and integrated modeling.
This course is highly recommended for AFE students and any Friedman student with an interest in economic aspects of the food/environment interface.
Second part of a two-semester sequence required of AFE students. This course covers the major biological, chemical and physical components of agricultural systems. Each is discussed from the viewpoints of both the underlying natural processes and principles, and their significance for major agricultural, food safety, and environmental policy issues in the US today. In this second semester, the topics are best management practices, livestock systems, food systems, climate change and bio-energy.
This course provides an advanced introduction to anthropological theory and methods designed for food and nutrition science and policy graduate students. Section 1 covers anthropology's four-field modes of inquiry, cross-cutting theoretical approaches and thematic interest groups, their respective institutions and intellectual concerns. Section 2 demonstrates applications of these concepts and methods to cutting-edge food and nutrition issues.
This course will cover knowledge of advanced Stata statistical computing, data base construction, error detection and correction, creation of composite variables, descriptive statistics, univariate analyses, regression analysis of continuous, binary and categorical outcomes, ANOVA & ANCOVA, analysis of clustered data including cluster randomized trials, panel data analysis & introduction to multilevel modeling, factor analysis; and the construction of scales and factor scores.
This course teaches principles and practical skills of qualitative methods in an interactive seminar format. Participants will learn how to design and carry out qualitative research by drawing on weekly background readings and writings, critical case-study discussions, and practical class exercises.