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Course Information
Course Unit Title : APPLIED LINEAR MODELS
Course Unit Code : 02EKO5114
Type of Course Unit : Optional
Level of Course Unit : Second Cycle
Year of Study : 1
Semester : 1.Semester
Number of ECTS Credits Allocated : 6,00
Name of Lecturer(s) : ---
Course Assistants : ---
Learning Outcomes of The Course Unit : To learn the fundementals of linear statistical models.
Mode of Delivery : Face-To-Face
Prerequisities and Co-requisities Courses : Unavailable
Recommended Optional Programme Components : Unavailable
Course Contents : Generalized inverse of matrices, Moore-Penrose conditions, Multivariate normal distribution of quadratic forms, Noncentral chi-square, Full rank models, Non full rank models, One way fixed effect classification model, Two way without interaction classification model, Estimable parametric functions.
Languages of Instruction : Turkish
Course Goals : To teach statistical models
Course Aims : To teach the fundementals of linear statistical models.
WorkPlacement   Not Available
Recommended or Required Reading
Textbook : Searl S.R., 1971, Linear Models, John Wiley & Sons Inc.
Additional Resources : Searl S.R., 1987, Linear Models for Unbalanced Data, John Wiley & Sons Inc. Moser B.K., 1996, Linear Models: A Mean Model Approach, Academic Press.
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 3 42  
Homeworks :
1 30 30  
Presentation :
1 20 20  
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 :
184  
Course's ECTS Credit :
6      
Assessment Methods and Criteria
Studies During Halfterm :
Number Co-Effient
Visa :
1 50
Quiz :
1 20
Homework :
1 30
Attendance :
0 0
Application :
0 0
Lab :
0 0
Project :
0 0
Workshop :
0 0
Seminary :
0 0
Field study :
0 0
   
TOTAL :
100
The ratio of the term to success :
50
The ratio of final to success :
50
TOTAL :
100
Weekly Detailed Course Content
Week Topics  
1 Matrix and determinant operations
 
2 Matrix inverses, trace of matrix, idempotent matrices
 
3 Moore-Penrose conditions, less than full rank matrices, pozitif and pozitif semi-definite matrices
 
4 Eigenvalues of matrix, eigenvectors
 
5 Quadratic forms, definitions, some theories
 
6 Distribution of quadratic forms
 
7 Independence of quadratic forms
 
8 Multivariate normal distrubition
 
9 Estimation problems in the full rank linear models, L.S.E. and M.L.E. of the model parameters
 
10 Variance estimation, hypothesis testing
 
11 Obtained of solution vectors in the less than full rank models, conditional inverse matrixes, some properties
 
12 Estimable function
 
13 Hypothesis testing in the less than full rank models
 
14 Applications in one-way classification desing with fixed effects with two-factor-design without interaction model