the Visiting Lecturer Program in Statistical Science

Objectives

A major theme of modern statistics is drawing conclusions from data. For example, biostatistical scientists are deeply involved in the planning and analysis of clinical trials that are evaluating the benefits of new therapies. These trials form the basis of the practice of "evidence based on medicine" and have profoundly affected the medical care system. Statistical quality control is widely practiced in manufacturing industries.

Probability modeling is used to design highly reliable systems from moderately reliable components. The chemical process industries use the methods of statistics to design experiments to determine the optimal combination of input variables to generate high product yields. The world of finance is fast changing due to the availability of data in real time. Trading on stock markets is experiencing a "revolution" with stock options and related derivative pricing becoming common tools for decision making. These tools are all based on statistical modeling.

Forensic science and the justice system are being very much influenced by probability calculations utilizing DNA evidence. The environmental sciences are concerned with evaluating the effects of air quality, contaminated water supplies and dumpsites on the health of the population. The estimation of adverse health events depends critically on statistical methods.

Whether forecasting is being carried out using probability forecasts. The widespread availability of computing has encouraged the creation of many large databases ranging from census data to mapping the human genome. One of the principal aims of statistical science is to develop methods of analysis to cope with the hundreds of variables in these databases and sort out the important variables that relate to outcomes of interest. Statistical science promises to be one of the emerging areas of the 21st century.

The career opportunities are rapidly expanding in academia, business, industry and government. The supply of statistical scientists cannot keep up with the growing demand.