Research Design and Analytical Methods in the Social Sciences

This course will introduce you to experiments and quasi-experiments in the social sciences. The emphasis is on designing experimental studies to achieve the highest calibre results to answer specific research questions common to quantitative research. Additionally, you will be introduced to the statistical analyses necessary for the data generated from an experimental design. This particular course will also explain how to conduct the necessary analyses using SPSS.

Following from a brief review of introductory statistics, the nature of experiments and causal inference will be discussed. This will include a discussion of common threats to validity and methods to assess the quality of the experimental (or quasi-experimental) design. Along with discussing true and quasi-experiments, this course will also address issues related to multiple regression. The focus will be on the types of research questions that can be answered with multiple regression analysis, and how these forms of observational/correlational studies are distinct from true experiments. Specific statistical analyses will be introduced, including 1-way, 2-way and factorial ANOVA; multiple comparison protocols for post hoc analyses; multiple regression for continuous and categorical predictors; ANCOVA; repeated measures ANOVA; mixed ANOVA designs; and hierarchical (nested) designs.

This course is designed for researchers who want to design experiments that provide generalizable findings. It is ideal for post-graduate students who are preparing proposal or programs of study for their degree. It is also ideal for professional researchers who want to increase their quantitative analysis research skill set.