This course introduces basic statistical concepts and their application to social science research. The themes include introduction to elementary statistics: data collection, organisation, presentation, analysis, frequency distribution; statistical measures of central tendency and dispersion, measures of correlations, measures of symmetry and skewness, simple linear regression; Statistical inferences: probability theory and distributions; discrete distributions (e.g. poisson, binomial), continuous probability distribution (e.g. normal), methods to check normality of population; Sampling procedures and distributions: random and non-random sampling distributions e.g. student t, Chi-square, F-distribution; Analysis of variables: univariate, bivariate and multivariate, ANOVA; Hypothesis testing: null and alternative hypotheses, level of significance, type one error, one tail and two tail tests; Analysis of variance; interpretation of factorial analysis with statistically significant interaction terms; multiple regression and analysis of variance and covariance; Social science statistical packages e.g. SPSS, STATA, and their application to data management.