Description

The seminar is optional, practically oriented, and addressed to graduate and Ph.D. students who are not familiar with the statistical package SPSS. Students familiarize themselves with the SPSS environment and basic data operations.

Through a series of practical exercises, they acquire basic knowledge about managing quantitative data for the purposes of statistical analysis. The seminar prepares students to attend advanced courses on statistical analysis using the SPSS. It consists of six two-hour sessions and concludes with one-hour recapitulation with exercises.

Topics – syllabus

1. Introduction: the SPSS environment, variable definitions (1st week)
2. Types of variables, data entry, and import from other applications (2nd week)
3. Calculating new variables, filters and variable transformation (3rd week)
4. Splitting, grouping, weighting data (4th week)
5. Tables & graphs – descriptive statistics (5th week)
6. Table & graph formatting – exporting tables & graphs (6th week)
7. Recapitulation with exercises (7th week)

Objectives

• To familiarize the students with the SPSS environment and some basic operations.
• To develop the skill to prepare a proper database for statistical analysis.
• To learn how to manage variables depending on the analysis pursued.

Readings & Links

More supportive material is available through e-learning. Some more detailed information on this seminar is also available on the web page of the Quality Assurance Unit of the Aristotle University.

1. SPSS Tutorials (1. Basics)
2. A PowerPoint file with some basic instructions (by Hui Bian)
3. A brief manual of SPSS 16.0 (by Petros Roussos & Giorgos Efstathiou, Athens University, Faculty of Philosophy, Pedagogy and Psychology)
4. Weighting a sample in SPSS (available only through e-learning)
5. A YouTube video with some introductory instructions
6. Dafermos, V. (2011). Social statistics and research methodology with SPSS (in Greek). Thessaloniki: Ziti. ISBN 978-960-456-279-4.

Procedure / evaluation

This seminar is optional and supportive. Students are engaged in practical exercises in the computer laboratory to achieve some familiarity with this particular working environment in introducing themselves to the logic of processing research data. Therefore, no exam, no grade evaluation, and no ECTS units. This seminar is not included in the prerequisites to complete the study cycle. However, a certificate of attendance is issued on demand.