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Information
| Code | IEM1815 |
| Name | Statistical Analysis I |
| Semester | . Semester |
| Duration (T+A) | 4-0 (T-A) (17 Week) |
| ECTS | 8 ECTS |
| National Credit | 4 National Credit |
| Teaching Language | Türkçe |
| Level | Doktora Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. EBRU ÖZGÜR GÜLER |
Course Goal
The purpose of this course is to bring the knowledge of how to make and interpret essential categorical data analysis.
Course Content
In this lesson decribes one way and two ways contingency table, general linear models, logistic regression and alternative modeling of binary response data will be covered.
Course Precondition
None
Resources
Multivariate Data Analysis, J.F. Hair, W.C. Black, B.J. Babin, R.E Anderson, 7th edition
Notes
Scientific articles that can be found online
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Differentiate categorical response data and ditributions for categorical data |
| LO02 | Finds contingency tables and two way contingency tables |
| LO03 | Recognized of general linear models and its variety |
| LO04 | Building logistic regression models |
| LO05 | Modelling alternative methods for binary response data |
| LO06 | Creates models for multinomial responses |
| LO07 | Building logninear models |
| LO08 | Evaluates clustered categorical data |
| LO09 | Examines other mixture models for discrete data |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Identify an econometric problem and propose a new solution to it | 2 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Develops new knowledge using current concepts in Econometrics, Statistics and Operations Research | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Explain for what purpose and how econometric methods are applied to other fields and disciplines | 2 |
| PLO04 | Beceriler - Bilişsel, Uygulamalı | Using her knowledge, brings original solutions to problems in Economics, Business Administration and other social sciences | |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Creates a new model using mathematics, statistics and econometrics knowledge to solve the problem encountered | 4 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Interprets the results obtained from the most appropriate method to predict the model | 4 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Performs conceptual analysis to develop solutions to problems | 5 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Collects data on purpose | |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Synthesizes the information obtained by using different sources within the framework of academic rules in a field that does not research | 4 |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Presents analysis results conveniently | |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Converts its findings into a master's thesis or a professional report in Turkish or a foreign language | 3 |
| PLO12 | Beceriler - Bilişsel, Uygulamalı | It researches current approaches and methods to solve the problems it encounters and proposes new solutions | |
| PLO13 | Beceriler - Bilişsel, Uygulamalı | Develops long-term plans and strategies using econometric and statistical methods | 3 |
| PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Performs self-study using knowledge of Econometrics, Statistics and Operations to solve a problem | 3 |
| PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Leads the team by taking responsibility | |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the necessity of lifelong learning, it constantly renews itself by following the current developments in the field of study | |
| PLO17 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution | |
| PLO18 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses a package program of Econometrics, Statistics, and Operation Research or writes a new code | 3 |
| PLO19 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Interprets the feelings, thoughts and behaviors of the related persons correctly/expresses himself/herself correctly in written and verbal form | |
| PLO20 | Yetkinlikler - Alana Özgü Yetkinlik | Applies social, scientific and professional ethical values | |
| PLO21 | Yetkinlikler - Alana Özgü Yetkinlik | Interprets data on economic and social events by following current issues | 3 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Motivation: Introduction of course contents and reference books | No preparation required | Öğretim Yöntemleri: Anlatım |
| 2 | Distributions for categorical data | Refer to textbook | Öğretim Yöntemleri: Anlatım |
| 3 | Contingency tables, comparing two proportions | Refer to textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 4 | Two way contingency tables | Refer to textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 5 | Testing interdependence in two way contingency tables | Refer to textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 6 | Generalized linear models | Refer to textbook | Öğretim Yöntemleri: Anlatım |
| 7 | Quasi likelihood models | Refer to textbook | Öğretim Yöntemleri: Anlatım |
| 8 | Mid-Term Exam | General review for the midterm exam | Ölçme Yöntemleri: Ödev |
| 9 | Logistic regression | Refer to textbook | Öğretim Yöntemleri: Anlatım |
| 10 | Alternative modelling of binary response data | Refer to textbook | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 11 | Models for multinomial responses | Refer to textbook | Öğretim Yöntemleri: Anlatım |
| 12 | Loglinear models for contingency tables | Refer to textbook | Öğretim Yöntemleri: Anlatım |
| 13 | Building and extending loglinear models | Refer to textbook | Öğretim Yöntemleri: Anlatım |
| 14 | Clustered categorical data | Refer to textbook | Öğretim Yöntemleri: Anlatım, Tartışma |
| 15 | Other mixture models for discrete data | Refer to textbook | Öğretim Yöntemleri: Anlatım, Tartışma |
| 16 | Term Exams | General review for the final exam | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | General review for the final exam | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 4 | 56 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 8 | 112 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 2 | 4 | 8 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 12 | 12 |
| Final Exam | 1 | 24 | 24 |
| Total Workload (Hour) | 212 | ||
| Total Workload / 25 (h) | 8,48 | ||
| ECTS | 8 ECTS | ||