Lund University

The course provides an introduction to the study of the Holocaust--the term used to describe the killing of the European Jews--and its causes and mechanisms. It also provides a basis for seeking answers to difficult questions, such as why this tragedy occurred. By examining the circumstances and mechanisms leading to genocide, and especially to the Holocaust, students are oriented on the post-war interpretations and debates. The effects of the Holocaust, how the Holocaust has affected post-war political and cultural discourses, and the reasons behind the delayed interest in it are also introduced. The Holocaust is also viewed in the context of other genocides committed both before and after World War II. Related lectures, readings, and seminars provide an overview of the Holocaust through empirical, chronological, theoretical, political, and other perspectives. Assessment is based on two short papers on elective readings related to the course topics and a take-home exam that is discussed at the final class meeting.

The course covers issues such as citizenship and representation in political institutions, changes in women’s participation in the labor force, sexuality and the social welfare state, masculinity studies as well as gender and social change. Integral to the course is learning to use critical theoretical understandings in analyzing how models of gender equality are affected by social relations such as race/ethnicity, sexual identity, and class. The course is directed towards international exchange students who wish to acquire knowledge of the Swedish/Scandinavian societies from a gender perspective, and it is also open for regular students at Lund University.

This course examines contemporary Japanese society, focusing on issues such as politics, pop culture, demographic change, and environment. The focus is on post-Cold War Japan, with special emphasis on the period after the earthquake, the tsunami, and the nuclear accident in 2011. Included are also the debate about Japan as an aging society with low fertility and the Japanese position with regard to immigration, gender, and hi-tech robotics.

The course contains four parts: managing logistics and operations system: value creation and strategic perspectives; designing industrial operations: products, processes, quality, and capacity; linkages to suppliers and customers: sourcing, purchasing, transportation, materials handling, and inventories; planning and controlling inventory and production in the supply chain: forecasting, long-term and short-term planning and control, and lean-based operations development.

This is an advanced course in linear and logistic regression, which expounds on the knowledge gained in introductory mathematical statistics courses. It covers matrix formulation of multivariate regression, methods for model validation, residuals, outliers, influential observations, construction and use of F- and t- tests, likelihood-ratio-test, confidence intervals and prediction, and applied implementation of various techniques in R software. Students also consider correlated errors, Poisson regression, multinominal and ordinal logistic regression. The first part of the course expands on previous study of linear regression to consider how to check if the model fits the data, what to do if it does not fit, how uncertain it is, and how to use it to draw conclusions about reality. The second part of the course explores logistic regression, which is used in surveys where the answers follow a categorical alternative pattern such as “yes/no,” “little/just fine/much,” or “car/bicycle/bus.” Students describe differences between continuous and discrete data, and the resulting consequences for the choice of statistical model. Students learn to give an account of the principles behind different estimation principles, and describe the statistical properties of such estimates as they appear in regression analysis. The interpretation of regression relations in terms of conditional distributions is studied. Odds and odds ration are presented, and students describe their relation to probabilities and to logistic regression. Students formulate both linear and logistic regression models for concrete problems, estimate and interpret the parameters, examine the validity of the model and make suitable modifications, use the model for prediction, utilize a statistical computer program for analysis, and present the analysis and conclusions of a practical problem in a written report and oral presentation. The course makes use of lectures, exercises, computer exercises, and project work.

This course is an advanced biology course providing an understanding of the fate, uptake, and effects of anthropogenic pollutants in the environment. Students study and apply ecotoxicological theories, models, and common methods and approaches concerning the fate of pollutants in the environment using fugacity-based multimedia partitioning models, uptake and accumulation using models of bioconcentration and biomagnification, and effects on different levels of biological organization (cellular, organism, population, and ecosystem) using ecotoxicological test methods with different endpoints.