Course Name Code Semester T+U Hours Credit ECTS
Regression Analysis I MAT 524 0 3 + 0 3 6
Precondition Courses Students are assumed to be familiar with Analysis I-II, Linear Algebra I-II, Probability, and Statistics
Recommended Optional Courses
Course Language Turkish
Course Level yuksek_lisans
Course Type Optional
Course Coordinator Doç.Dr. NESRİN GÜLER
Course Lecturers
Course Assistants Res.Assist. Emre Kişi
Course Category
Course Objective Applied studies are constructed on the theory. Regression analysis is an often used tool in the statisticians toolbox. The purpose of this course is to give the theory of regression analysis.
Course Content Vectors of random variables. Multivariate normal distribution. Linear regression: Estimation and distribution theory. The F-test. Confidence intervals and regions. Departures from underlying assumptions.
# Course Learning Outcomes Teaching Methods Assessment Methods
1 He/she consolidates the concept of random variables. Lecture, Question-Answer, Self Study, Testing, Homework,
2 He/she sees multivariate normal distribution. Lecture, Question-Answer, Discussion, Self Study, Testing, Homework, Project / Design,
3 He/she uses the method of least squares for estimation of parameter. Lecture, Question-Answer, Drilland Practice, Motivations to Show, Self Study, Testing, Homework, Project / Design,
4 He/she understands the generalization of the method of least squares and he/she recognizes that it is different from the old one. Lecture, Question-Answer, Drilland Practice, Motivations to Show, Self Study, Testing, Homework, Project / Design,
5 He/she understands and to apply the methods of estimation. Lecture, Question-Answer, Drilland Practice, Motivations to Show, Self Study, Testing, Homework,
6 He/she understands estimation and distribution theories in linear regression. Lecture, Question-Answer, Drilland Practice, Self Study, Testing, Homework, Project / Design,
7 He/she tests various hypothesis. Lecture, Question-Answer, Drilland Practice, Self Study, Testing, Homework, Project / Design,
8 He/she constructs confidence regions. Lecture, Question-Answer, Drilland Practice, Motivations to Show, Self Study, Testing, Homework, Project / Design,
9 He/she understands biased estimation. Lecture, Question-Answer, Drilland Practice, Self Study, Testing, Homework, Project / Design,
Week Course Topics Preliminary Preparation
1 Vectors of random variables [1] pages 1-15
2 Multivariate normal distribution [1] pages 17-24
3 Multivariate normal distribution (continuation) [1] pages 24-31
4 Linear regression: Estimation and distribution theory [1] pages 35-44
5 Least squares estimation [1] pages 35-44
6 Generalized least squares estimation [1] pages 69-70
7 Design matrix of less than full rank [1] pages 62-64
8 Estimation with linear restrictions [1] pages 59-62
9 Other methods of estimations [1] pages 77-88
10 Linear regression: Hypothesis testing [1] pages 97-99
11 The F-test [1] pages 99-116
12 Confidence intervals and regions [1] pages 119-129
13 Confidence intervals and regions (continuation) [1] pages 129-136
14 Departures from underlying assumptions [1] pages 227-230
Resources
Course Notes [1] Seber, G. A. F., Linear Regression Analysis, John Wiley, New York, 1977.
Course Resources [2] Johnson, R. A. and Wichern, D. W., Applied Multivariate Statistical Analysis, Englewood Cliffs, New Jersey, 1982.
[3] Searle, S. R., Matrix Algebra Useful For Statistics, Canada, 1982.
[4] Searle, S. R., Linear Models, John Wiley and Sons, Inc., New York, 1971.
[5] Graybill, F. A., Introduction to Matrices with Applications in Statistics, United States, 1969.
[6] Graybill, F. A., An Introduction to Linear Statistical Models, Volume 1, Mc Graw-Hill Book Co., New York, 1961.
Order Program Outcomes Level of Contribution
1 2 3 4 5
2 Student follows the current journals in his/her field and puts forward problems. X
2 Student follows the current journals in his/her field and puts forward problems. X
3 Student understands the relations between the disciplines pertaining to the undergraduate programs of Mathematics X
3 Student understands the relations between the disciplines pertaining to the undergraduate programs of Mathematics X
4 Student gets new knowledge by relating the already acquired experience and knowledge with the subject-matters out of his/her field. X
4 Student gets new knowledge by relating the already acquired experience and knowledge with the subject-matters out of his/her field. X
5 Student uses different proof methods to come to a solution by analyzing the problems encountered. X
5 Student uses different proof methods to come to a solution by analyzing the problems encountered. X
6 Student determines the problems to be solved within his/her field and if necessary takes the lead. X
6 Student determines the problems to be solved within his/her field and if necessary takes the lead. X
7 Student conveys, in team work, his/her knowledge in the studies done in different disciplines by applying the dynamics pertaining to his/her own field. X
7 Student conveys, in team work, his/her knowledge in the studies done in different disciplines by applying the dynamics pertaining to his/her own field. X
8 Student critically evaluates the knowledge got at the bachelor´s degree level, makes up the missing knowledge and focuses on the current subject-matters X
8 Student critically evaluates the knowledge got at the bachelor´s degree level, makes up the missing knowledge and focuses on the current subject-matters X
9 Student knows a foreign language to communicate orally and in writing and uses the foreign language in a way that he/she can have a command of the Maths terminology and can do a source research. X
9 Student knows a foreign language to communicate orally and in writing and uses the foreign language in a way that he/she can have a command of the Maths terminology and can do a source research. X
10 Student improves himself/herself at a level of expertness in Mathematics or in the fields of application by improving the knowledge got at the bachelor´s degree level. X
10 Student improves himself/herself at a level of expertness in Mathematics or in the fields of application by improving the knowledge got at the bachelor´s degree level. X
10 Student improves himself/herself at a level of expertness in Mathematics or in the fields of application by improving the knowledge got at the bachelor´s degree level. X
11 Student considers the scientific and cultural ethical values in the phases of gathering and conveying data or writing articles. X
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 40
1. Ödev 20
1. Performans Görevi (Seminer) 40
Total 100
1. Yıl İçinin Başarıya 60
1. Final 40
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 15 15
Assignment 1 8 8
Performance Task (Seminar) 1 20 20
Final examination 1 20 20
Total Workload 159
Total Workload / 25 (Hours) 6.36
dersAKTSKredisi 6