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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS ELECTIVE

Offered By

PSYCHOLOGY

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

ASSOCIATE PROFESSOR DUYGU GÜNGÖR CULHA

Offered to

PSYCHOLOGY

Course Objective

The aim of this course is to introduce multivariate data methods. Within the scope of the course, advanced multivariate statistical method applications will be carried out.

Learning Outcomes of the Course Unit

1   1. Define multivariate statistical models 2   2. Use multivariate statistics appropriate to the data 3   3. Interpret advanced multivariate statistics 4   4. To be able to plan multivariate research 5   5. To be able to perform Monte Carlo simulation studies in multivariate models 6   6. Compare different multivariate models

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to the course and its requirements 2 Multiple regression 3 Covariance Analysis 4 Multivariate analysis of variance 5 Multivariate analysis of variance 6 Multivariate analysis of covariance 7 Midterm Exam 8 Multilevel linear modeling 9 Multilevel regression 10 Multilevel regression applications 11 Visualization of multivariate models 12 Reporting multivariate models 13 Presentations 14 Review of the course

Recomended or Required Reading

Grimm, L.G. & Yarnold, P.R. (2002). Reading and understanding mutivariate statistics, APA Pubications, Washington. Grimm, L.G. & Yarnold, P.R. (2002). Reading and understanding more mutivariate statistics, APA Pubications, Washington. Tabachnick B.G. & Fidell, L.S. (2013). Using Multivariate Statistics, Pearson Publication, London.

Planned Learning Activities and Teaching Methods

Lesson Presentation Question and Answer Homework Discussion

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 STT TERM WORK (SEMESTER) 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.20 + FIN* 0.50 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.20 + RST* 0.50

Further Notes About Assessment Methods

None

Assessment Criteria

LO 1-6: It will be evaluated by midterm exam, homework/presentation and final exam.

Language of Instruction

English

Course Policies and Rules

Attendance to 70% of the lectures is compulsory.

Contact Details for the Lecturer(s)

duygu.gungor@deu.edu.tr

Office Hours

Tuesday 14:00-15:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Preparations before/after weekly lectures 14 4 56 Preparation for midterm exam 1 6 6 Preparation for final exam 1 5 5 Preparation for quiz etc. 1 5 5 Preparing assignments 1 4 4 Final 1 1 1 Midterm 1 1 1 TOTAL WORKLOAD (hours) 120

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 LO.1 5 5 5 LO.2 5 5 5 LO.3 5 5 5 LO.4 5 5 5 LO.5 5 5 5 LO.6 5 5 5