Course Information
TitleΣΤΑΤΙΣΤΙΚΗ ΙΙ / STATISTICS II
CodeΨΥ-400
FacultyPhilosophy
SchoolPsychology
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CommonNo
StatusActive
Course ID600013505

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

Registered students: 170
OrientationAttendance TypeSemesterYearECTS
KORMOSElective Courses426

Class Information
Academic Year2019 – 2020
Class PeriodSpring
Faculty Instructors
Weekly Hours4
Class ID
600144504
Type of the Course
  • Scientific Area
Course Category
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
Prerequisites
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).
Keywords
ANOVA, non parametric methods, Non-parametric ANOVA, reliability, principal component analysis, SPSS
Educational Material Types
  • Notes
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Description
Hands-on learning of SPSS in the computer lab
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures783
Reading Assigment240.9
Tutorial261
Interactive Teaching in Information Center261
Exams20.1
Total1566
Student Assessment
Description
Written assessment
Student Assessment methods
  • Written Exam with Short Answer Questions (Summative)
  • Written Exam with Problem Solving (Summative)
Bibliography
Course Bibliography (Eudoxus)
Ανάλυση δεδομένων με το IBM SPSS Statistics 21. Συγγραφέας: Γναρδέλλης Χαράλαμπος, ΕΚΔΟΣΕΙΣ ΠΑΠΑΖΗΣΗΣ ΑΕΒΕ. Κωδικός Βιβλίου στον Εύδοξο: 33133182
Additional bibliography for study
Σημειώσεις Στατιστικής ΙI, Σημειώσεις Στατιστικής για το SPSS.
Last Update
11-10-2020