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| IST3001 | Linear Models | 4+0+0 | ECTS:6 | | Year / Semester | Fall Semester | | Level of Course | First Cycle | | Status | Elective | | Department | DEPARTMENT of STATISTICS and COMPUTER SCIENCES | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 4 hours of lectures per week | | Lecturer | Prof. Dr. Zafer KÜÇÜK | | Co-Lecturer | None | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | To give necessary theoric information for undergraduate and graduate education. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | express linear models in matrix notation | 1,4,8 | 1, | | LO - 2 : | do matrix operations for estimation of linear models | 1,4,8 | 1, | | LO - 3 : | gain linear modelling rationale, parameter estimates and statistical inference for these estimators | 1,4,8 | 1, | | LO - 4 : | model any kind of data, and they will be able to tests of hypothesis | 1,4,8 | 1, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Quadratic Forms And Distributions Of Some Special Quadratic Forms; Matrix Formulation Of The Full Rank Models; Parameter Estimation And Hypothesis Tests Of The Full Rank Models |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Basic matrix operations, transpose and notations of vectors for linear models | | | Week 2 | Orthogonality and inverses of matrices, eigenvalues and eigenvectors for linear models | | | Week 3 | Ranks, traces of matrices and idempotent matrices for linear models | | | Week 4 | Quadratic forms, expectation of random vector or matrix and variance-covariance matrix of random vectors, distributions of some special quadratic forms for linear models | | | Week 5 | Using chi-square, student-t and F distributions in linear models, independence of quadratic forms | | | Week 6 | Matrix formulation of the full rank models, parameter estimation of the full rank models | | | Week 7 | Estimation of variance for the full rank models, confidence intervals of estimators and their functions | | | Week 8 | Problem solving | | | Week 9 | Midterm exam | | | Week 10 | Problem solving | | | Week 11 | Joint confidence region for regression coefficients in the full rank models | | | Week 12 | Hypothesis testing for regression coefficients in the full rank models, partial and squential tests and hypothesis test for subvectors of regression coefficients | | | Week 13 | Parameter estimation and hypothesis tests in less than full rank models, | | | Week 14 | Reparameterization in in less than full rank models | | | Week 15 | Problem solving | | | Week 16 | Final exam | | | |
| 1 | Akdeniz, F. ve Öztürk, F. 1996, Lineer Modeller, A.O.F.F. Döner Sermaye İşletmesi Yayınları No: 38, Ankara | | | |
| 1 | Rencher, Alvin C.,2008, Linear Models in Statistics, John Wiley&Sons, INC., 2nd ed., New York, USA | | | 2 | Myers and Milton 1991, A First Course in the Theory of Linear Statistical Models , PWS-KENT | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9. hafta | 21.11.2021 | 1.5 | 50 | | End-of-term exam | 16.hafta | 12.01.2022 | 1.5 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 4 | 14 | 56 | | Sınıf dışı çalışma | 5 | 14 | 70 | | Laboratuar çalışması | 0 | 0 | 0 | | Arasınav için hazırlık | 10 | 1 | 10 | | Arasınav | 1.5 | 1 | 1.5 | | Uygulama | 0 | 0 | 0 | | Klinik Uygulama | 0 | 0 | 0 | | Ödev | 4 | 4 | 16 | | Proje | 0 | 0 | 0 | | Kısa sınav | 0 | 0 | 0 | | Dönem sonu sınavı için hazırlık | 20 | 1 | 20 | | Dönem sonu sınavı | 1.5 | 1 | 1.5 | | Diğer 1 | 0 | 0 | 0 | | Diğer 2 | 0 | 0 | 0 | | Total work load | | | 175 |
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