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Course Information
Course Unit Title : Multi Variate Data Analysis
Course Unit Code : 01END5109
Type of Course Unit : Optional
Level of Course Unit : Second Cycle
Year of Study : Preb
Semester : 255.Semester
Number of ECTS Credits Allocated : 6,00
Name of Lecturer(s) : ---
Course Assistants :
Learning Outcomes of The Course Unit : Faced with a complex business problem to model and solve the problem using the student determine which of these techniques,
Find solution
Used to decide which solution may be in adequacy.
Mode of Delivery : Face-To-Face
Prerequisities and Co-requisities Courses : Unavailable
Recommended Optional Programme Components : Unavailable
Course Contents : Network modeling, goal programming, integer programming, dynamic programming, deterministic inventory models, probability, forecasting models, game theory, simulation and Markov Chains
Languages of Instruction : Turkish
Course Goals : System analysis
In order to examine the behavior of the model and interpret building and gain the ability to do experiments.
Course Aims : Students in the business world will confront the production, marketing, finance, accounting, human resources, planning, inventory management, such as the different functions the problem of advanced mathematical and statistical techniques using the model is to solve, and solving by interpreting business decisions to help you be able to. For this purpose, from computers to take advantage and in particular spreadsheet program with the problem of modeling and solution finding essential will be.
WorkPlacement   Not Available
Recommended or Required Reading
Textbook : Lecture Notes
Additional Resources :
Material Sharing
Documents :
Assignments :
Exams :
Additional Material :
Planned Learning Activities and Teaching Methods
Lectures, Practical Courses, Presentation, Seminar, Project, Laboratory Applications (if necessary)
ECTS / Table Of Workload (Number of ECTS credits allocated)
Student workload surveys utilized to determine ECTS credits.
Activity :
Number Duration Total  
Course Duration (Excluding Exam Week) :
14 3 42  
Time Of Studying Out Of Class :
14 4 56  
Homeworks :
6 3 18  
Presentation :
0 0 0  
Project :
0 0 0  
Lab Study :
0 0 0  
Field Study :
0 0 0  
Visas :
1 20 20  
Finals :
1 30 30  
Workload Hour (30) :
30  
Total Work Charge / Hour :
166  
Course's ECTS Credit :
6      
Assessment Methods and Criteria
Studies During Halfterm :
Number Co-Effient
Visa :
1 50
Quiz :
0 0
Homework :
0 0
Attendance :
0 0
Application :
0 0
Lab :
0 0
Project :
0 0
Workshop :
0 0
Seminary :
0 0
Field study :
0 0
   
TOTAL :
50
The ratio of the term to success :
50
The ratio of final to success :
50
TOTAL :
100
Weekly Detailed Course Content
Week Topics  
1 Introduction to Multivariate Analysis
 
2 Matrix Algebra and Random Vectors
 
3 Random Sampling
 
4 Multivariate Normal Distribution
 
5 Conclusions Related to the Average Vector
 
6 Many Multivariate Comparison of Mean
 
7 Multivariate Linear Regression Models I
 
8 Multivariate Linear Regression Models II
 
9 Basic Components
 
10 Factor Analysis I
 
11 Factor Analysis II
 
12 Canonical Correlation Analysis I
 
13 Canonical Correlation Analysis II
 
14 Classification