GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
MULTİVARİATE STATİSTİCS/5221303
Course Title: MULTİVARİATE STATİSTİCS
Credits 3 ECTS 7.5
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
Student gain skill at theroretical and applied multivariate statistical methods used in different areas.
Student learns various multivariate statistical methods with the help of statistical softwares (R, Matlab, SPSS…) and can easily apply these methods.
Student can relevantly use multivariate statistical analyses for any study.
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE
1. Week  Multivariate data structures and multivariate distributions
2. Week  Hypothesis tests for mean vectors
3. Week  Graphical displays for multivariate data
4. Week  Multivariate variance and covariance analyses
5. Week  Profile analysis: Multivariate approaches for repeated measures
6. Week  Cluster analysis
7. Week  Discriminant analysis
8. Week  Mid-term – Logistic regression analysis
9. Week  Reliability analysis, principal components and factor analyses
10. Week  Multidimensional scaling analysis and correspondance analysis
11. Week  Multivariate regression analysis
12. Week  Canonical correlation analysis
13. Week  Path analysis
14. Week  Project presentations
15. Week  Final exam
16. Week  -
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
30
 Assignment
0
0
 Application
0
0
 Projects
1
20
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
50
 Percentage of Final Exam to Total Score  
50
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
7
5
35
 Searching in Internet and Library
6
4
24
 Material Design and Implementation
2
3
6
 Report Preparing
4
3
12
 Preparing a Presentation
4
3
12
 Presentation
4
2
8
 Midterm Exam and Preperation for Midterm Exam
5
4
20
 Final Exam and Preperation for Final Exam
7
4
28
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
187
 TOTAL WORKLOAD / 25: 
7.48
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1X
2X
3X
4X
5X
6X
7X
8X
9X
10X
 -- NAME OF LECTURER(S)
   (Assoc. Prof. Hülya OLMUŞ)
 -- WEB SITE(S) OF LECTURER(S)
   (https://abs.gazi.edu.tr/hulya)
 -- EMAIL(S) OF LECTURER(S)
   (hulya@gazi.edu.tr)