Type: Elective course
Curriculum: Mass Media
Semesters: E and higher
Co-teaching: N. Tsigilis
Description
The course educates students in statistical tests and the management of quantitative data files using dedicated software. It focuses on elementary statistical tests and analyses employed in quantitative research in the social sciences.
Participating in a series of practical exercises on data from actual surveys, students introduce themselves to basic data operations. At the same time, they familiarize themselves with elementary statistical tests and with the interpretation and presentation of the results, particularly in scholarly papers. The course emphasizes particularly those statistical tests that are useful in research for preparing a graduation thesis. It also provides the knowledge necessary to understand the results of surveys often presented in public discourse, such as opinion polls and other types of quantitative research. This way, the course supports the development of students' ability to read and interpret such publications critically.
The course is laboratory-based and therefore – once chosen – attendance is mandatory. The classes include several summing-up and reiteration exercises. Students learn also how to collect, enter, and manage quantitative data.
Topics – syllabus (indicative)
- Introduction: presentation of course procedures and content
- Basic operations with data files; types of variables
- Data transfer between different applications, descriptive statistics of one variable
- Graphs
- Result tables, descriptives of one variable grouped by another one
- Splitting and grouping data, modifying variables
- The normal distribution, the sample mean distribution, the definition and the use of Z-values
- Comparing the mean of one sample
- Comparing the means of two samples
- Correlation analysis of quantitative variables
- Correlation analysis of nominal variables
- Data analysis for the final paper
Objectives
- This course aims to provide students with basic knowledge and skills for statistical analysis of quantitative data
- It aims to teach them how to design and develop proper files for data entry and how to import data from quantitative surveys
- To provide them with the knowledge necessary for statistical tests using dedicated software
- To develop the background necessary for checking and verifying the data assumptions for each statistical test
- Finally, the course aims to provide the knowledge needed to understand when and how to use some of the most common statistical tests.
Textbook
Additional readings
More supportive material is available on the e-learning system, as well as in the full-text databases accessed through the Aristotle University user network. Some more detailed information on this course is also available on the web page of the Quality Assurance Unit of the Aristotle University.
Batsidis, A. D. (2014). Statistical analysis of data using SPSS: Teaching notes [In Greek]. Ioannina: University of Ioannina, Department of Mathematics.
Chalikias, M., Manolesou, A., & Lalou, P. (2015). Research methodology and introduction to statistical data analysis using IBM SPSS Statistics [In Greek]. Athens: Kallipos Publications.
Cleophas, T. J., & Zwinderman, A. H. (2010). SPSS for starters. Dordrecht: Springer Netherlands.
Gerber, S. B., & Finn, K. V. (2005). Using SPSS for Windows: Data analysis and graphics (2nd ed.). New York: Springer-Verlag.
Goss-Sampson, M. A. (2019). Statistical analysis in JASP: A guide for students (2nd ed.). Greenwich: University of Greenwich, Centre for Science and Medicine in Sport & Exercise
Mooi, E., & Sarstedt, M. (2019). A concise guide to market research: The process, data, and methods using IBM SPSS Statistics. Berlin, Heidelberg: Springer.
Roussos, P., & Efstathiou, G. (2008). A short guide to SPSS 16.0 [In Greek]. Athens: University of Athens, Faculty of Philosophy, Pedagogy, and Psychology.
Procedure / evaluation
The course is elective. Attendance - once chosen - is mandatory because it is laboratory-based and it is carried out using computers in the Department laboratories. The evaluation is based on an in-class exam consisting of a practical application using a computer. Information about the next exam session, exam dates and essay due-dates can be found in the announcements page (provided that the exam dates have been announced).