STATISTICS METHODS FOR DATA ANALYSIS

Course Information
TitleΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ ΔΕΔΟΜΕΝΩΝ / STATISTICS METHODS FOR DATA ANALYSIS
CodeIS20
FacultySciences
SchoolInformatics
Cycle / Level1st / Undergraduate, 2nd / Postgraduate
Teaching PeriodWinter
CoordinatorEleftherios Angelis
CommonNo
StatusActive
Course ID40002448

Programme of Study: PPS School of Informatics (2014-today)

Registered students: 14
OrientationAttendance TypeSemesterYearECTS
TECΗNOLOGIES GNŌSĪS DEDOMENŌN KAI LOGISMIKOUElective Courses belonging to the selected specialization117.5
TECΗNOLOGIES PLĪROFORIAS KAI EPIKOINŌNIŌN STĪN EKPAIDEUSĪElective Courses117.5
PSĪFIAKA MESA- YPOLOGISTIKĪ NOĪMOSYNĪElective Courses117.5
DIKTYAKA SYSTĪMATAElective Courses117.5

Programme of Study: PPS of School of Informatics (2013-today)

Registered students: 0
OrientationAttendance TypeSemesterYearECTS
Information SystemsCompulsory Course117.5
Information And Communication Technologies In EducationElective Courses117.5
Digital MediaElective Courses117.5
Communication Systems and TechnologiesElective Courses117.5

Programme of Study: PPS Informatics 2

Registered students: 0
OrientationAttendance TypeSemesterYearECTS
Information SystemsCompulsory Course117.5
Information and Communication Technologies in EducationElective Courses117.5
Digital MediaElective Courses117.5
Communication Systems and TechnologiesElective Courses117.5
Class Information
Academic Year2016 – 2017
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Class ID
600039937
Course Type 2016-2020
  • Scientific Area
  • Skills Development
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Probability and Statistics, Linear Algebra
Learning Outcomes
Understanding complex statistical concepts and methods using statistical software
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Work in teams
  • Work in an interdisciplinary team
  • Generate new research ideas
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Statistical analysis of multivariate data with SPSS. Data types and variables. Introduction and data management in SPSS. Descriptive and graphical methods. Contingency tables of categorical variables. Statistical tests and comparison of samples. Correlation, multiple regression and analysis of variance. Multivariate data analysis. Factor analysis. Discriminant analysis. Cluster analysis.
Keywords
Statistics, multivariate data, hypothesis testing, data analysis, SPSS
Educational Material Types
  • Notes
  • Slide presentations
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Laboratory Teaching
Description
Teaching using statistical software
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures1003.3✓
Laboratory Work1254.2✓
Total2257.5
Student Assessment
Description
Final project assignment (40%) and written examinations (60%)
Student Assessment methods
  • Written Assignment (Formative)
Bibliography
Course Bibliography (Eudoxus)
Discovering Statistics Using SPSS. Andy Field,2005, SAGE Publications
Additional bibliography for study
Σημειώσεις του διδάσκοντα, διαφάνειες
Last Update
31-03-2016