The course deals mainly with descriptive statistics. In the course lectures, reference is made to the introductory concepts of types of statistical data and data collection methods , basic characteristics of numerical data, introduction and understanding of probabilities, the normal distribution and understanding of sampling, hypothesis testing, as well as, correlations and simple linear regression.

The aim of the course is to understand the basic statistical concepts and methods of descriptive statistics. Furthermore, it scopes to develop a statistical/ way of thinking and analyzing quantitative and qualitative data with an emphasis on familiarity with modern methods and tools for managing and analyzing this data.

The laboratory part of the course includes the following sections:

  • Statistical analysis, graph creation, data presentation.
  • Analysis of survey data from Google-type platforms.
  • Learning SPSS.
  • Data entry.
  • Descriptive statistics.
  • Description of variables.
  • Inductive statistics.
  • x2 test.
  • t-test.
  • One way Anova.
  • Simple linear regression reliability analysis.

Upon successful completion of the course, students will:

  • Understand basic principles of statistical science.
  • Learn the required SPSS functions.
  • Be able to analyze statistical data using statistical packages, extracting reliable conclusions for future research.
Code Course Semester C / Ε Theory (hours) Lab (hours) ECTS
601Y Personal Data and Privacy 6 C 4 5
602Y Internet and Electronic Publishing 6 C 4 5
603Y Statistical Methods and Applications 6 C 2 2 5
Selection 2 out of 4
604EY Project Management 6 Ε 3 5
605EY Digital Arts and Entertainment 6 Ε 3 5
606EY Corporate Social Responsibility 6 Ε 3 5
607EY Social Media and Journalism 6 Ε 3 5
Selection 1 out of 2
608EY Digital Marketing II 6 Ε 2 2 5
609ΕΥ Electronic Commerce 6 Ε 2 2 5