University of Hong Kong

A time series consists of a set of observations on a random variable taken over time. Time series arise naturally in climatology, economics, environment studies, finance and many other disciplines. The observations in a time series are usually correlated; the course establishes a framework to discuss this. This course distinguishes different type of time series, investigates various representations for the processes and studies the relative merits of different forecasting procedures. Students will analyze real time-series data on the computer. Topics: Stationary and the autocorrelation functions; linear stationary models; linear non-stationary models; model identification; estimation and diagnostic checking; seasonal models and forecasting methods for time series. 

This course examines the roles of logistics in supply chain management. It covers business of production; business environment; transport fundamentals and transport decisions; storage and handling systems and decisions; inventory policies; forecasting logistics requirements; facility location analysis; network planning process; purchasing scope and objectives; purchasing structure and organization; purchasing variables – price, time and quality; buying commodities; buying capital goods; buying services; purchasing systems. 

This course examines critical and creative texts that engage with narrative ethics as they appear in different cultural and linguistic traditions. This focus on ethics will simultaneously redirect us back to narrativity and the constructedness of texts.

This course examines the essential areas in biomedical engineering, including technologies and applications in life sciences and medicine. The course is broadly divided into 4 areas: biomechanics and biomaterial; cell and tissue engineering; biomedical instrumentations and signals, and medical imaging. The global development and other issues, such as safety, ethics and industry will also be addressed.

This course examines the principles and techniques related to the formation, dispersion and control of various air pollutants formed from anthropogenic pollution sources. Topics include: micrometeorology; air dispersion; combustion fundamentals; pollutant formation mechanism and control technologies; abatement of volatile organic compounds using incineration techniques; particulate and aerosol abatement technology; particle technology, log-normal distribution; settling chamber; cyclone; electrostatic precipitator; and bag filter. 

This course examines fundamental concepts in probability and mathematical statistics, including probabilistic modelling, limiting results, estimation and hypothesis testing. Topics include random variables and vectors, distribution and quantile functions, covariance and correlation matri-ces, strong law of large numbers, central limit theorem, estimators and their (asymptotic) properties, parametric estimators (maximum likelihood, method of moments), (asymptotic) conĄdence intervals (mean and variance of a normal, difference of means of two normals, ratio of means of two normals), hypothesis tests (theory, power function, p-value, asymptotic tests, likelihood ratio tests). 

This course examines philosophical issues concerning knowledge and the mind. These include metaphysical questions about what minds are, such as whether the mind is something non-physical, and questions about what knowledge is and how (and whether) we can obtain it. We will also cover questions about the existence of god, the possibility of free will, and personal identity.

The analysis of variability is mainly concerned with locating the sources of the variability. Many statistical techniques investigate these sources through the use of linear models. This course presents the theory and practice of these models. Topics include: simple linear regression: least squares method, analysis of variance, coefficient of determination, hypothesis tests and confidence intervals for regression parameters, prediction; multiple linear regression: least squares method, analysis of variance, coefficient of determination, reduced versus full models, hypothesis tests and confidence intervals for regression parameters, prediction, polynomial regression; one-way classification models: one-way ANOVA, analysis of treatment effects, contrasts; two-way classification models: interactions, two-way ANOVA for balanced data structures, analysis of treatment effects, contrasts, randomized complete block design; universal approach to linear modeling: dummy variables, multiple linear regression representation of one-way and two-way (unbalanced) models, ANCOVA models, concomitant variables; regression diagnostics: leverage, residual plot, normal probability plot, outlier, studentized residual, influential observation, Cook's distance, multicollinearity, model transformation. 

This course examines American hemispheric history, society, and culture across North and South America. The course will introduce significant social and cultural developments in selected countries of the Americas. Topics will include indigenous - colonial relations; slavery and its legacies; the impact of modernity on society and culture; the struggle for civil rights in 20th and 21st centuries; wars and empire; immigration, forced migration and its impact on politics; globalization and neoliberal economics; and the rise of populist nationalism in the 21st century.