ISB552 Generalized Linear Models

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code ISB552
Name Generalized Linear Models
Term 2024-2025 Academic Year
Semester . Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Doktora Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. MAHMUDE REVAN ÖZKALE


Course Goal / Objective

To gain knowledge of measurement and theory in the context of modern probability theory.

Course Content

Distributions from exponential family, maximum likelihood method, logistic and poisson regression models, linear mixed models

Course Precondition

none

Resources

Agresti, A. 2016. Foundations of Linear and Generalized Linear Models. (Wiley Series in Probability and Statistics) 1st Edition

Notes

lecture notes


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Develop and deepen the current and advanced knowledge in the field of statistics based on master qualifications by original thought and / or research and at the level of expertise and reach original definitions that will bring innovation to the field
LO02 Understands the interdisciplinary interaction related to the science of statistics; it achieves original results using knowledge requiring expertise in analysis, synthesis and evaluation of new and complex ideas
LO03 Evaluates, uses and transfers new information in the field of statistics with a systematic approach
LO04 Gains high level skills to use research methods in studies related to statistics.
LO05 Develops a new idea, method, design and / or application that brings innovation to the field of statistics by using acquired skills, or applies a known idea, method, design and / or application to a different field, researches, comprehends, designs and applies an original topic
LO06 Contributes to progress in the field by conducting an original study that brings innovation to the field of statistics, develops a new idea, method, design and / or application, or applies a known idea, method, design and / or application
LO07 Extends the boundaries of knowledge in its field by publishing at least one scientific article in the field of statistics in national and / or international refereed journals and / or producing or interpreting an original work. Makes leadership in environments that require the analysis of original and interdisciplinary problems
LO08 Develops new ideas and methods related to the field by using high level mental processes such as creative and critical thinking, problem solving and decision making
LO09 Defends original opinions in discussing the subjects in the field of statistics and uses the necessary languages and technologies to communicate effectively in the field
LO10 Uses the knowledge, problem solving and / or application skills that they assimilate in the field of statistics in interdisciplinary studies
LO11 Develops strategy, policy and implementation plans and evaluates the results. Functional interaction by using strategic decision-making processes in solving problems encountered in relation to statistics
LO12 Introduces scientific, technological, social or cultural advancements in the field of statistics and contributes to the process of being a society of knowledge and sustaining it. In addition, it contributes to the solution of social, scientific, cultural and ethical problems encountered in the field of statistics and supports the development of these values


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Develops new methods and strategies in modeling statistical problems and generating problem-specific solutions. 5
PLO02 Bilgi - Kuramsal, Olgusal Can do detailed research on a specific subject in the field of statistics. 4
PLO03 Bilgi - Kuramsal, Olgusal Have a good command of statistical theory to contribute to the statistical literature. 4
PLO04 Bilgi - Kuramsal, Olgusal Can use the knowledge gained in the field of statistics in interdisciplinary studies. 5
PLO05 Yetkinlikler - Öğrenme Yetkinliği Can organize projects and events in the field of statistics.
PLO06 Yetkinlikler - Öğrenme Yetkinliği Can perform the stages of creating a project, executing it and reporting the results. 5
PLO07 Beceriler - Bilişsel, Uygulamalı Have the ability of scientific analysis. 4
PLO08 Bilgi - Kuramsal, Olgusal Can produce scientific publications in the field of statistics. 4
PLO09 Bilgi - Kuramsal, Olgusal Have analytical thinking skills. 5
PLO10 Yetkinlikler - Öğrenme Yetkinliği Can follow professional innovations and developments both at national and international level. 4
PLO11 Yetkinlikler - Öğrenme Yetkinliği Can follow statistical literature.
PLO12 Beceriler - Bilişsel, Uygulamalı Can improve his/her foreign language knowledge at the level of making publications and presentations in a foreign language. 5
PLO13 Bilgi - Kuramsal, Olgusal Can use information technologies at an advanced level. 3
PLO14 Bilgi - Kuramsal, Olgusal Have the ability to work individually and make independent decisions. 5
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have the qualities necessary for teamwork. 3
PLO16 Bilgi - Kuramsal, Olgusal Have a sense of professional and ethical responsibility. 2
PLO17 Bilgi - Kuramsal, Olgusal Acts in accordance with scientific ethical rules. 2


Week Plan

Week Topic Preparation Methods
1 Distributions related to the normal distribution, quadratic forms, model fitting and fundamentals of model fitting Reading the related references Öğretim Yöntemleri:
Anlatım
2 Notations for explanatory variables, exponential family and the properties of distributions in exponential family Reading the related references Öğretim Yöntemleri:
Anlatım
3 Introduction to generalized linear models, important distributions in generalized linear models Reading the related references Öğretim Yöntemleri:
Anlatım
4 Maximum likelihood estimation and examples, Quasi-likelihood Reading the related references Öğretim Yöntemleri:
Anlatım
5 Sampling distribution for score statistics, Taylor series approximations, sampling distibution for maximum likelihood distributions Reading the related references Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
6 Log-likelihood ratio statistic, sampling distibution for deviance, hypothesis testing Reading the related references Öğretim Yöntemleri:
Anlatım
7 Residual analysis in generalized linear models Reading the related references Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
8 Mid-Term Exam Review the topics discussed in the lecture notes and sources Ölçme Yöntemleri:
Ödev
9 Binary variables and logistic regression Reading the related references Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
10 Nominal and ordinal logistic regression Reading the related references Öğretim Yöntemleri:
Anlatım
11 Poisson regression Reading the related references Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
12 Linear mixed models, estimation in linear mixed models Reading the related references Öğretim Yöntemleri:
Anlatım
13 Inference for regression coefficients and variance components in linear mixed models Reading the related references Öğretim Yöntemleri:
Anlatım
14 Conditional and marginal expectations in linear mixed models, diagnostic measures Reading the related references Öğretim Yöntemleri:
Anlatım
15 Generalized linear mixed models Reading the related references Öğretim Yöntemleri:
Anlatım
16 Application on generalized linear models Review the topics discussed in the lecture notes and sources Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Review the topics discussed in the lecture notes and sources Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 09.05.2024 02:16