Contact Brian
Brian Schultz
413.549.4600
Brian Schultz
Associate Professor Emeritus of Entomology and Ecology
Brian Schultz, associate professor emeritus of ecology and entomology, received a B.S. in zoology, an M.S. in biology, and a Ph.D. in ecology from the University of Michigan.
An agricultural ecologist and entomologist who does research at the Hampshire College Farm Center, Schultz has spent a number of years in Central America and the Caribbean studying methods of insect pest control. He is also interested in statistical analysis and world peace.
Recent and Upcoming Courses
-
This course examines agriculture as a set of ecological systems and related social aspects, focusing on organic and/or sustainable production methods, and agroecology. It refers to ecology in the sense of interactions between organisms (e.g., pests and predators; wildlife) and the larger sense of environmental impacts (e.g., pollution; climate change), along with key related social issues and solutions (e.g., power relationships; government subsidies). A broad range of topics will be covered, including: pest control alternatives (e.g., pesticides; biocontrols); soil ecology, fertility, erosion, and carbon sequestration; animals in agriculture; genetically modified crops; biofuels; farm labor; global vs. local trade; economic influences; power bottlenecks; and more. Course work will consist of readings, discussion, writings, lab and farm work/observations, and projects, tailored to individual student experience, interests, and goals. Field work will include our College farm and forest, and trips to other local farms and habitats. KEYWORDS:Sustainable, agriculture, ecology, agroecology, organic
-
This course is an introduction to descriptive and inferential statistics with examples drawn primarily from the fields of medicine, public health, and ecology. The approach is applied and hands-on; students are expected to complete two problem sets each week, collect and analyze data as a class, and design and carry out their own examples of each analysis in four review exercises. We cover description, estimation and hypothesis testing (z-scores, t-tests, chi-square, correlation, regression, and analysis of variance). More advanced techniques such as multi-way ANOVA and multiple regression are noted but not covered in detail. We also discuss the role of statistics in causal inference though the emphasis of the course is on practical applications in design and analysis. The course text is The Basic Practice of Statistics by David S. Moore and the primary software is Minitab.Keywords:Statistics,research design,quantitative analysis