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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS PSI 6105 DESCRIPTIVE ANALYSIS WITH R ELECTIVE 3 0 0 5

Offered By

PSYCHOLOGY

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR SERAP AKFIRAT

Offered to

PSYCHOLOGY

Course Objective

The aim of this course is to enable students to carry out analyzes of psychometric measurement using the R program.

Learning Outcomes of the Course Unit

1   1. To be able to define psychometry plugins of R programming language 2   2. Ability to use different data types 3   3. Ability to carry out all descriptive analyzes with R 4   4. Ability to test item functional difference 5   5. Ability to simulate Monte Carlo 6   6. Ability to summarize study results using R

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 1 Introduction of the course and its requirements 2 2 R media 3 3 R Studio 4 4 R commander 5 5 Introduction to Lavaan 6 6 Structural equation practice with Lavaan 7 7 Midterm Exams 8 8 LMest package 9 9 MICE package applications 10 10 RShiny packs 11 11 Monte Carlo Applications 12 12 Monte Carlo Applications 13 13 Presentations 14 14 Lesson review

Recomended or Required Reading

Field,A., Miles, J. & Field Z. (2012). Discovering statistics using R, Sage Pub., UK.

Planned Learning Activities and Teaching Methods

Lesson Presentation Q&A 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 with midterm exam, homework/presentation and final exam.

Language of Instruction

Turkish

Course Policies and Rules

Attendance at 70% of the classes is obligatory.

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