IEM1839 Advanced Statistical Methods

8 ECTS - 4-0 Duration (T+A)- . Semester- 4 National Credit

Information

Code IEM1839
Name Advanced Statistical Methods
Term 2022-2023 Academic Year
Term Spring
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. GÜLSEN KIRAL
Course Instructor
1


Course Goal / Objective

The purpose of this course is to teach complex and advanced statistical techniques and the applications of these advanced techniques with scientific articles and presentations to students.

Course Content

This lesson covers Continuous distributions (exponential, gamma, beta, normal distributions), probability integral transformation, changing variables, multivariate distributions, Central Limit Theorem, sampling distributions,order statistics, regression and ANOVA, the parameters of non-statistical applications, multivariate regression, multivariate discriminant analysis, logistic regression, MANOVA, MANCOVA, unified analysis, cluster analysis.

Course Precondition

There are no prerequisites.

Resources

Books, articles, computers, etc.

Notes

1-Miller, I. and M. Miller (2004). Mathematical Statistics with Applications , Pearson Education 2-amprit Chatterjee, Ali S. Hadi Bertham Price (2000) “Regression Analysis by Example” Rawlings, John O. (1988). Applied Regression Analysis: A Research Tool , Wadsworth and Brooks3-Reha Alprar 2003 .”Uygulamalı Çok Değişkenli İstatistiksel Yöntemlere Giriş 1 “4-Mendenhall, W. and T. Sincich (1996). A Second Course in statistics: Regression Analysis , Prentice Hall.


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Explains complex and advanced statistical techniques.
LO02 It makes inferences about the applications of these advanced techniques with scientific articles and presentations.
LO03 Runs statistical package programs.
LO04 Explains data using package programs.
LO05 Statistical comments about the proposed model.
LO06 Makes inferences about statistical information.
LO07 Defines continuous distributions.
LO08 Performs probability integral transformation.


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 3
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 3
PLO04 Beceriler - Bilişsel, Uygulamalı Using her knowledge, brings original solutions to problems in Economics, Business Administration and other social sciences 3
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 4
PLO08 Beceriler - Bilişsel, Uygulamalı Collects data on purpose 5
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 3
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 2
PLO12 Beceriler - Bilişsel, Uygulamalı It researches current approaches and methods to solve the problems it encounters and proposes new solutions 3
PLO13 Beceriler - Bilişsel, Uygulamalı Develops long-term plans and strategies using econometric and statistical methods 2
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 2
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 3
PLO17 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution 2
PLO18 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses a package program of Econometrics, Statistics, and Operation Research or writes a new code
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 3
PLO20 Yetkinlikler - Alana Özgü Yetkinlik Applies social, scientific and professional ethical values 4
PLO21 Yetkinlikler - Alana Özgü Yetkinlik Interprets data on economic and social events by following current issues 2


Week Plan

Week Topic Preparation Methods
1 Continuous distributions (exponential, gamma, beta, normal distributions) Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
2 Continuous distributions Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
3 Changing variables with multivariate distributions, Central Limit Theorem Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
4 Sampling distributions Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
5 Order statistics Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
6 Statistical Inference Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
7 examination Examining the relevant chapter in the book Öğretim Yöntemleri:
Alıştırma ve Uygulama
8 Mid-Term Exam Examining the relevant chapter in the book Ölçme Yöntemleri:
Yazılı Sınav
9 Regression and ANOVA Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
10 Parameters of non-statistical applications, multivariate regression Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
11 Multivariate discriminant analysis Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
12 Logistic regression Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
13 MANOVA, MANCOVA Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
14 Unified analysis Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
15 Cluster analysis Examining the relevant chapter in the book Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
16 Term Exams Examining the relevant chapter in the book Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Examining the relevant chapter in the book 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

Update Time: 17.11.2022 09:16