This subject prepares students for research using quantitative methods commonly used in health and social sciences. The subject starts with the research design process and then delves into quantitative methods used to isolate cause and effect in the presence of (potentially unobserved) confounding relationships. Confounding relationships are endemic to health and social science research. Experimental data collection is the preferred method, however it is often unfeasible or unethical. Alternatives include matching, difference-in-differences, instrumental variable and regression discontinuity analysis. Students will learn how these methods neutralize the effects of confounders, which of these methods to use under which circumstances and apply that knowledge analysing big (cross-sectional) data sets. Findings from this type of quantitative research are often crucial elements in decision-making processes in business (ex-ante cost benefit analysis), public policy (social return on investment analysis) and public health policy (cost effectiveness analyses).

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Admission to (BComm Hons) Offerings: All

BU4054 - Research Methods and Statistics

Research Methods and Statistics

Apply these methods to big (cross sectional) data sets

Evaluate the array of quantitative methods available to deal with confounding relationships

Summarize the relevance of the outcomes of above methods for public/private decision making