INTERNATIONAL BURCH UNIVERSITY
Graduate Study - Faculty of Economics and Social Sciences
Management PhD
2013-2014

SYLLABUS
Code Name Level Year Semester
BUS 663 Advanced Statistics Graduate 1 Spring
Status Number of ECTS Credits Class Hours Per Week Total Hours Per Semester Language
7.5 124 English

Instructor Assistant Coordinator
Ali GÖKSU, Assoc. Prof. Dr. Ali GÖKSU, Assoc. Prof. Dr.
[email protected] no email

COURSE OBJECTIVE
This applied course is designed for graduate students with a prior background in statistics. This means that students should have considerable experience with multiple regression and an ability to conduct such analyses using some statistical software. The major topics of the course will include hierarchical linear modeling and structural equation modeling. This course aims at refreshing the statistical knowledge of the students and presenting advanced statistical methods which will possibly be needed during dissertation and further academic studies.

COURSE CONTENT
Week
Topic
  1. Introduction
  2. Factor Analysis
  3. Multiple Regression Analysis
  4. Discrimination, classification and pattern recognition
  5. Logistic Regression
  6. Multivariate Analysis of Variance (MANOVA)
  7. Conjoint Analysis
  8. Cluster Analysis
  9. Multidimensional Scaling
  10. Correspondence Analysis
  11. Structural Equations Modeling: An Introduction
  12. Confirmatory Factor Analysis (SEM)
  13. Testing a Structural Model (SEM)
  14. Presentation

LABORATORY/PRACTICE PLAN
Week
Topic

    TEACHING/ASSESSMENT
    Description
    • Lectures
    • Practical Sessions
    • Excersises
    • Presentation
    • Self Evaluation
    • Project
    • Assignments
    • Case Studies
    Description (%)
    Method Quantity Percentage (%)
    Homework
    Project
    Midterm Exam(s)
    Presentation20
    Term Paper40
    Final Exam140
    Total: 100
    Learning outcomes
    • Students will be able to understand the professional research literature, conduct quantitative research, contribute to the growing body of economic science knowledge and reach their full potential as scientists.
    TEXTBOOK(S)
    • Multivariate Data Analysis, 7/E
    • Joseph F. Hair, Jr
    • William C. Black
    • Barry J. Babin
    • Rolph E. Anderson
    • ISBN-10: 0138132631 • ISBN-13: 9780138132637
    • ©2010 • Prentice Hall • Cloth, 816 pp
    • Published 02/13/2009

    ECTS (Allocated based on student) WORKLOAD
    Activities Quantity Duration (Hour) Total Work Load
    Lecture (14 weeks x Lecture hours per week)16348
    Laboratory / Practice (14 weeks x Laboratory/Practice hours per week)16116
    Midterm Examination (1 week)12020
    Final Examination(1 week)13030
    Preparation for Midterm Examination11010
    Preparation for Final Examination7.50
    Total Workload: 124
    ECTS Credit (Total workload/25): 5