Information Package / Course Catalogue
Generalized Linear Models
Course Code: BİS534
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 6
Objectives of the Course

To provide advanced students in statistics, biostatistics with a course of study in the theory and practice of modern extensions of the general linear statistical model.

Course Content

Advanced topics and types in generalized linear models, structure of data, theory and applications of parameter estimate methods. Logistic regression, Poisson regression, analysis of dependent data, generalized estimating equations, the exponential family, the linear predictor, link functions, analysis of deviance, parameter estimation, residuals. Model choice, fitting and validation.

Name of Lecturer(s)
Learning Outcomes
1.To learn basic concepts and basic structure of generalized linear model
2.Learning the principles and methods of statistical modeling for generalized linear models
3.To be able to make linear transformations
4.To learn factor interactions, aggregate and aggregate models
5.To be able to establish a generalized linear model using statistical softwares and evaluate these models
Recommended or Required Reading
Weekly Detailed Course Contents
Week 1 - Theoretical
Exponential Distribution Family and Properties
Week 2 - Theoretical
Exponential Distribution Family and Properties
Week 3 - Theoretical
Basic structure of generalized linear models
Week 4 - Theoretical
Estimation for generalized linear models
Week 5 - Theoretical
Inference for generalized linear models
Week 6 - Theoretical
The basic structure of logistic regression models
Week 7 - Theoretical
Prediction and inference in the logistic regression models
Week 8 - Intermediate Exam
Midterm exam
Week 9 - Theoretical
The basic structure of log-linear models
Week 10 - Theoretical
Prediction and inference in the log-linear models,
Week 11 - Theoretical
Establishing linear and generalized linear model in R, estimation and inference
Week 12 - Theoretical
Establishing a logistic regression model in R
Week 13 - Theoretical
Prediction and inference of a logistic regression model in R
Week 14 - Theoretical
Establishing log-linear models in R, prediction and inference
Week 15 - Theoretical
Literature review and discussion
Week 16 - Final Exam
Final exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140342
Assignment110010
Individual Work80216
Quiz142142
Midterm Examination120222
Final Examination120222
TOTAL WORKLOAD (hours)154
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
OÇ-1
OÇ-2
OÇ-3
OÇ-4
OÇ-5
3
4
3
4
3
4
4
3
3
5
Adnan Menderes University - Information Package / Course Catalogue