Course Information
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
Course ID600013505

Programme of Study: PPS Tmīmatos PSychologías (2017-sīmera)

Registered students: 133
OrientationAttendance TypeSemesterYearECTS
KORMOSElective Courses426

Class Information
Academic Year2022 – 2023
Class PeriodSpring
Instructors from Other Categories
Weekly Hours4
Total Hours52
Class ID
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Distance learning
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
General Prerequisites
There are no prerequisites for the course
Learning Outcomes
Upon successful completion of the course, students are expected to: 1. Be able to choose, apply and explain statistical methods that are appropriate for data coming from relatively complex experimental research. This is accomplished by dealing with numerical examples and exercises. 2. Acquire basic knowledge to be able to assess the main psychometric characteristics of a psychological test on the basis of particular statistical methods. 3. Acquire the appropriate knowledge and skills to apply the statistical package SPSS in order to enter, transform and analyze data of an empirical research and explain the results applying the statistical methodology that has been taught in the courses Statistics I and II.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work autonomously
  • Work in teams
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Introduction to ANOVA. One-way analysis of variance, one-way analysis of variance with repeated measures, effect size, introduction to multiple comparisons, Scheffe’s test. Introduction to two-way ANOVA and the analysis of higher order experimental designs. Non-parametric statistical methods: Mann-Whitney U test, Sign test, Wilcoxon signed-rank test, Spearman’s rank-order correlation. Non-parametric analysis of variance: Kruskal-Wallis test, Friedman test, Cochran’s Q test, non-parametric tests for multiple comparisons. Reliability of measurements, methods of estimating reliability, Cronbach and Kuder-Richardson coefficients of internal consistency. Introduction to principal component analysis. Statistical data analysis using SPSS (in the computer lab).
ANOVA, non parametric methods, Non-parametric ANOVA, reliability, principal component analysis, SPSS
Educational Material Types
  • Notes
  • Video lectures
  • Multimedia
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Teaching of SPSS.
Course Organization
Reading Assigment240.9
Interactive Teaching in Information Center261
Student Assessment
Written assessment
Student Assessment methods
  • Written Exam with Short Answer Questions (Summative)
  • Written Exam with Problem Solving (Summative)
Course Bibliography (Eudoxus)
Ανάλυση δεδομένων με το IBM SPSS Statistics 21. Συγγραφέας: Γναρδέλλης Χαράλαμπος, ΕΚΔΟΣΕΙΣ ΠΑΠΑΖΗΣΗΣ ΑΕΒΕ. Κωδικός Βιβλίου στον Εύδοξο: 33133182. Μεθοδολογία εκπαιδευτικής έρευνας με στοιχεία Στατιστικής. Συγγραφέας: Σταμοβλάσης Δημήτρης, ΕΚΔΟΤΗΣ: ΜΑΡΚΟΥ ΚΑΙ ΣΙΑ Ε.Ε. Κωδικός βιβλίου στον Εύδοξο: 59377804.
Additional bibliography for study
Σημειώσεις Στατιστικής ΙI, Σημειώσεις Στατιστικής για το SPSS.
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