TÜRKÇE
ENGLISH
Information
| Code | ISB542 |
| Name | Regression Theory - II |
| 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 | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. MAHMUDE REVAN ÖZKALE |
Course Goal / Objective
To enable students with the ability to do models for multiple regression models and perform the adequacy analysis
Course Content
Multiple linear regression, model adequacy checking, correcting model inadequacies, diagnostics for leverages and influence, polynomial regression models
Course Precondition
none
Resources
Montgomery, D. C., Peck, E. A., Vining, G. G. (2001), Introduction to Linear Regression Analysis, 3rd edition, John Wiely and Sons Inc.
Notes
lecture notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Fits model with indicator variable |
| LO02 | Selects variable and fits best model |
| LO03 | Solves multicollinearity problem |
| LO04 | Does performance adequacy analysis |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Have in-depth theoretical and practical knowledge about Probability and Statistics | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | They have the knowledge to make doctoral plans in the field of statistics. | 4 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Has comprehensive knowledge about analysis and modeling methods used in statistics. | 5 |
| PLO04 | Bilgi - Kuramsal, Olgusal | Has comprehensive knowledge of methods used in statistics. | 3 |
| PLO05 | Bilgi - Kuramsal, Olgusal | Make scientific research on Mathematics, Probability and Statistics. | 3 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Indicates statistical problems, develops methods to solve. | 4 |
| PLO07 | Bilgi - Kuramsal, Olgusal | Apply innovative methods to analyze statistical problems. | 3 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Designs and applies the problems faced in the field of analytical modeling and experimental researches. | 5 |
| PLO09 | Bilgi - Kuramsal, Olgusal | Access to information and do research about the source. | 2 |
| PLO10 | Bilgi - Kuramsal, Olgusal | Develops solution approaches in complex situations and takes responsibility. | 3 |
| PLO11 | Bilgi - Kuramsal, Olgusal | Has the confidence to take responsibility. | 2 |
| PLO12 | Beceriler - Bilişsel, Uygulamalı | They demonstrate being aware of the new and developing practices. | 2 |
| PLO13 | Beceriler - Bilişsel, Uygulamalı | He/She constantly renews himself/herself in statistics and related fields. | 5 |
| PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Communicate in Turkish and English verbally and in writing. | 2 |
| PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Transmits the processes and results of their studies clearly in written and oral form in national and international environments. | |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | It considers the social, scientific and ethical values in the collection, processing, use, interpretation and announcement stages of data and in all professional activities. | 4 |
| PLO17 | Yetkinlikler - Öğrenme Yetkinliği | Uses the hardware and software required for statistical applications. | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | General concept of indicator variables and comments on the use of indicator variables | Reading the related references | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 2 | Indicator variable with more than two factors, more than one indicator variable | Reading the related references | Öğretim Yöntemleri: Anlatım |
| 3 | Regression approach to analysis of variance | Reading the related references | Öğretim Yöntemleri: Anlatım |
| 4 | Model building problem, consequences of model misspecification, criteria for evaluating subset regression models | Reading the related references | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 5 | All posible regression models | Reading the related references | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 6 | Sources and effects of multicollinearity | Reading the related references | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 7 | Detection of multicollinearity | 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: Yazılı Sınav |
| 9 | Ridge regression | Reading the related references | Öğretim Yöntemleri: Anlatım |
| 10 | Relationship between the ridge regresiion and other estimators, ridge regression and variable selection | Reading the related references | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 11 | Generalized ridge regression, principal components regression | Reading the related references | Öğretim Yöntemleri: Anlatım |
| 12 | Nonlinear regression models, nonlinear least squares, transformation to linear model | Reading the related references | Öğretim Yöntemleri: Anlatım |
| 13 | Parameter estimation in a nonlinear system | Reading the related references | Öğretim Yöntemleri: Anlatım |
| 14 | Logistic regression | Reading the related references | Öğretim Yöntemleri: Anlatım |
| 15 | Poisson regression | Reading the related references | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 16 | Regression models with autocorrelated errors | Reading the related references | 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 | ||