Introduction to SPSS

Short Bio Gregor Petrič, Ph.D., is an associate professor for social informatics and a researcher in the Center for Methodology and Informatics at the Faculty of Social Sciences, University of Ljubljana. He lectures topics in social informatics, methodology of social science research, online communities, Internet and society, and new media. His current research focuses on online community governance, social media and empowerment, measurement of online phenomena, and methodological issues in researching online communities and social media. Prerequisite knowledge Note from the Academic Convenors to prospective participants: by registering to this course, you certify that you possess the prerequisite knowledge that is requested to be able to follow this course. The instructor will not teach again these prerequisite items. If you doubt whether you possess that knowledge to a sufficient extent, we suggest you contact the instructor before you proceed to your registration. This course is best suited for students who have only little or no experience with SPSS and have elementary knowledge of the quantitative methodology of social sciences and statistics. Students should have basic computer skills (file management, basic web skills) and be acquainted with the very elementary statistics (concepts like mean, variance, ratio). Short course outline The course is intended for participants who wish to become competent in using SPSS as a tool for organising and manipulating data, performing basic statistical analyses and designing tabular and graphical presentation of results. The course will begin by familiarising with the user interface (practical example, structure of program, settings, menus, toolbars) and proceed in three broad topics: 1. organising and manipulating data (unit/variable structure, import and export of data, selecting and finding data, manipulating and computing variables); 2. basic statistical analyses (distributions and measures of central tendency, exploratory analyses, tables, comparisons); and 3. graphical presentation of results (designing various plots, adding/removing plot elements, editing plots). The course will be accompanied with relevant practical exercises on different datasets (mostly GSS, ESS and GGP). This course is best suited for students who have only little or no experience with SPSS.