Statistical Analyses in Social Research Inprinciples, Methods and Computer Applications

 Mimes x office document icon PROGRAMME: Undergraduate
CATEGORY: Compulsory with option
ΚΩΔΙΚΟΣ 110360  

Description ― The course is offered in English but key terms and concepts will also be translated in Greek if needed. In this course students learn in an applied way key issues and challenges of statistical data analysis in social sciences and humanities and become familiar in a practical way on essential requirements of empirical scientific research.

Week 1

Introduction to quantitative social research

Week 2

Overview of methods and tools

Week 3

Data processing

Week 4

Descriptive statistics

Week 5

Introduction to inferential statistics

Week 6

Chi-square test

Week 7

Correlation analyses

Week 8

Simple linear regression

Week 9

Multiple linear regression

Week 10


Week 11

Anova tests

Week 12

Factor analysis

Week 13

Ethics in quantitative research

The objectives of the course ― The course aims to introduce students to the methods and techniques of statistical analysis of social research data using statistical applications.

Expected learning outcomes ― Upon successful completion of the course students will be able: To define the meaning and uses of measurement in the social sciences and humanities.

Indicate what measurement scale is and distinguish different types of measurement scales.

To understand the concepts of sample and population in sampling, realize the importance of the representativeness of the sample, distinguish basic types of random sampling and understand the concepts of sample distribution and the sampling error.

To understand the importance and use of statistical hypotheses.

To code quantitative data for statistical analysis using specific statistical applications.

To apply descriptive statistical data analysis.

To become aware of the data requirements when applying statistical tests on relationships.

To select and apply appropriate statistical test(s) to examine the relationship between variables.

To interpret the statistical analysis results.

To write short research reports based on the statistical results.

Bibliography  ― OpenStax (2016). Introductory Statistics. Download for free at The study materials related to each assignment will be posted with the description of the assignment each week. Regarding the main social/political topics that we are going to explore and discuss during the course you will need to study the following papers, particularly their introductory sections where there is a review of the relevant literature:

Attitudes towards Immigration/Immigrants

Markaki, Y., & Longhi, S. (2013). What determines attitudes to immigration in European countries? An analysis at the regional level. (see also published text in Migration Studies, 1(3), 311-337).

Meuleman, B. (n.d.). The evolution of anti-immigration attitudes. ESS Education net.

Salamońska, J. (2016). Friend or Foe? Attitudes Towards Immigration from Other European Union Countries. SocietàMutamentoPolitica, 7(13), 237-253.

Trust towards state/democratic institutions

Hakhverdian, A., & Mayne, Q. (2012). Institutional trust, education, and corruption: A micro-macro interactive approach. The Journal of Politics, 74(03), 739-750.

Marien, S. (2011). Measuring Political Trust Across Time and Space. In: Hooghe M., Zmerli , S. (Eds.), Political Trust. Why Context Matters. (pp. 13-46). Colchester: ECPR Press.

van Elsas, E. (2015). Political trust as a rational attitude: A comparison of the nature of political trust across different levels of education. Political Studies, 63(5), 1158-1178. (you can download this paper using the Panteion University wifi connection)

Evaluation methods ― During the semester, students will be required to deliver about 7-8 weekly assignments and present a paper chosen from the selected bibliography. The assessment does not include final examinations. The assessment criteria will be included in the description of each assignment which will be accessible to the students from the course site.

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