This course introduces applied analysis of survey, administrative and other types of data of interest to social science researchers. The course is divided into two parts. The first part deals with statistical inference involved in survey data analysis from a practical perspective. The focus will be on the specification of models including choice of control variables, the interpretation of results, handling missing data, and the challenges posed by reverse causality, omitted variable bias, endogeneity, and other issues that commonly arise in the analysis of social data. The second part introduces analytical strategies for “unconventional” data types, such as social network, web data, and plain texts. Special attention will be given to challenges to social scientists regarding data extraction, data integration, and visualization.