FACULTY OF SCIENCES
ACTUARIAL
Course Name   Regression Analysis (Elective)
Semester Course Code Theoretical / Practice time ECTS
6 2717621 2 / 0 5
Course Degree Bachelor's degree
Course Language Turkish
Format of Delivery: Face to Face
Course Coordinator Prof. Dr. Mehmet Fedai KAYA
Coordinator e-mail fkaya selcuk.edu.tr
Instructors
Asistant Instructors
Course Objectives Multiple regression analysis of the properties, to understand the purpose and place of use
Basic Sciences Engineering Scinces Social Sciences Educational Sciences Artistic sciences Medical Science Agricultural sciences
30 70 0 0 0 0 0
Course Learning Methods and Techniquies
The course will be held in the classroom in the form of mutual subject expression, homework and discussion.
Week Course Content Resource
1 Conditional expected value and the concept of regression, the normal distribution and its properties Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
2 Simple linear regression model and least squares estimators of the parameters Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
3 Matrix representation, the least squares estimators of the parameters of the dispersion acteristics, BLUE, estimation and residues Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
4 ANOVA Table preparation Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
5 Examination of model assumptions (residual analysis)) Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
6 Changing variability and weighted least squares method, autocorrelation, normal probability plots, Box-Cox transformations Confidence intervals and hypothesis tests about the parameters Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
7 Multiple regression and the estimators of the regression parameters, properties of estimators Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
8 The ion of appropriate regression model, the AIC and BIC Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
9 Dispersions of quadratic forms Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
10 Midterm Exam
11 Stepwise methods, regression and polynomial regression MİNMAD Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
12 The multiple bond (multicolllinearity) to remedy the problems and multiple correlation methods Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
13 Ridge regression Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
14 Exercises Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
15 Overview Applied Regression Analysis: A Research Tool , Wadsworth & Brooks.
Assesment Criteria   Mid-term exam Final exam
  Quantity Percentage Quantity Percentage  
Term Studies : - - - -
Attendance / Participation : - - - -
Practical Exam : - - - -
Special Course Exam : - - - -
Quiz : - - - -
Homework : - - - -
Presentations and Seminars : - - - -
Projects : - - - -
Workshop / Laboratory Applications : - - - -
Case studies : - - - -
Field Studies : - - - -
Clinical Studies : - - - -
Other Studies : - - - -
Mid-term exam   1 40 - -
Final exam   - - 1 60
ECTS WORK LOAD TABLE   Number Duration
Course Duration : 14 2
Classroom Work Time : 14 6
Presentations and Seminars : - -
Course Internship : - -
Workshop / Laboratory Applications : - -
Field Studies : - -
Case studies : - -
Projects : - -
Homework : - -
Quiz : - -
Mid-term exam : 1 18
Final Exam : 1 20
ECTS 5
No COURSE LEARNING OUTCOMES CONTRIBUTION
D.Ö.Ç. 1 Confidence intervals and hypothesis testing on the parameters to apply 4
D.Ö.Ç. 2 Regression model to 4
D.Ö.Ç. 3 ANOVA tables and learn how to prepare 4
D.Ö.Ç. 4 Estimating the model parameters 3
D.Ö.Ç. 5 By examining data and graphs to understand the ion of the most appropriate model 3
* 1: Zayıf - 2: Orta - 3: İyi - 4: Çok İyi
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