# COURSE UNIT TITLE

: CATEGORICAL DATA ANALYSIS

#### Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
PSI 5085 CATEGORICAL DATA ANALYSIS ELECTIVE 3 0 0 8

PSYCHOLOGY

#### Level of Course Unit

Second Cycle Programmes (Master's Degree)

#### Course Coordinator

PROFESSOR ABBAS TÜRNÜKLÜ

PSYCHOLOGY

#### Course Objective

The aim of this course is to introduce the basics of psychometrine. In the course, concepts related to classical test theory will be examined.

#### Learning Outcomes of the Course Unit

 1 Being able to define basic concepts related to categorical data analysis. 2 Being able to explain main categorical data analysis models 3 Being able to give examples recent research on the categorical data analysis 4 Being able to pursue and contribute to current research in the subject of the categorical data analysis

Face -to- Face

None

None

#### Course Contents

 Week Subject Description 1 Statistical Models for Categorical Variables 2 Regression toward the mean and tendency toward the mode 3 factor analysis with categorical indicators 4 factor analysis with categorical indicators 5 factor analysis with categorical indicators 6 Logistic models 7 Midterm 8 Logistic models 9 Logistic models 10 cross tabulation 11 cross tabulation 12 mutli categorical variables 13 DINA Model 14 DINA Model

#### Recomended or Required Reading

Van der Ark, L.A., Croon, M.A. & Sijtsma, K. (2005). New developments in categorical data analysis for the social and behavioural sciences, Lawrence Erlbaum Associates, London.
Çilan, Ç.A. (2009). Sosyal bilimlerde kategorik verilerle ilişki analizi, Pegem Akademi, Ankara.

Lesson
Question-Answer
Presentation
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 * 0.30 + FIN* 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40

None

#### Assessment Criteria

LO 1-2: They will be evaluated by questions in the midterm examination
LO 3-5:They will be evaluated by questions in the final examination

Turkish

#### Course Policies and Rules

Attendance must be at least %70 for the lecture.

To be announced.

To be announced.

None

#### Workload Calculation

 Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparations before/after weekly lectures 13 7 91 Preparation for midterm exam 1 10 10 Preparation for final exam 1 14 14 Preparing presentations 13 4 52 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 212

#### Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.155444
LO.245444
LO.35544444
LO.44544444