The course will equip student with adequate theoretical background, content and statistical tools and techniques required for analyses of quantitative research data. For each of the statistical tools and techniques the objective is to provide opportunities for students to develop a conceptual understanding of what that statistical tool is, when to use it (including the underlying assumptions and how to test them), how to use it, and how to interpret the results. Students will be exposed to the use of Predictive Analytics Software (PASW) and Microsoft Excel to run the various analyses. Topics include: The Power of Statistical Test; Point-Biserial Correlation; Multivariate analysis of variance – MANOVA, Analysis of covariance – ANCOVA; Analysis of covariance – ANCOVA; Scale Construction- levels of measurement,  factor analysis, cyclical scale refinement; Multiple regression analysis; Structural Equation Modelling; Cluster analysis; Effect Size and Post Hoc Analyses; Various non-parametric statistics: Mann-Whitney, Wilcoxon, Friedman & Kruskal Wallis, Logistic Regression and Kendall’s concordance will also be discussed.