This course examines the key elements of undertaking a research project with an empirical flavour, and provides guidance on the use of various statistical tools and techniques in the analysis of data. The course is not designed as a replacement for more formal and deeper analysis of specific statistical methods. Rather, it is a refresher for those seeking to revive their basic research skills and also serves as an introduction for those seeking to go onto further study in specific statistical techniques. The course would be of interest to Honours and Postgraduate students and should complement studies that involve statistical method and/or research projects.

Section 1: The Research Process (Introduction to Research Theory, Development of Knowledge, Steps in the Research Process)

Section 2: Sourcing Relevant Information (Information Resources, Literature Review, Referencing, DataStream Tutorial)

Section 3: Data Gathering (Bias, Precision and Relevance, Types of Data, Handling Missing Data)

Section 4: Data Presentation Techniques (Identification of Data Structure, Graphical Description, Numerical Description

Section 5: Review of Hypothesis Testing Ideas (Statistical Questions: Populations versus Samples, Confidence Intervals, Structure of Hypothesis Tests, Developing Hypotheses, Decision-Making and Types of Error)

Section 6: Analysis and Applications (Deciding on the Type of Test, Specifying an Appropriate Model, Assessing Model Assumptions and Fit, Model Revision and Issues of Robustness, Computer-based Applications)

By the end of this unit, students are expected to have attained proficiency in the following areas:

• Be able to design and deliver research proposals and reports;
• Be able to appraise research articles and presentations; and,
• Be able to locate and analyse data from a number of well-known sources.

Assessment is based on a research proposal to be submitted at the end of the term.

See Course Website