Dokuz Eylül University Information Package / Courses Catalog

Description of Individual Course Units

Course Unit Code	Course Unit Title	Type Of Course	D	U	L	ECTS
STA 5075	REGRESSION ANALYSIS	ELECTIVE	3	0	0	7

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR NESLIHAN DEMIREL

Offered to

Statistics (English)
STATISTICS (ENGLISH)
Statistics (English)

Course Objective

The objective is to study general models in regression analysis and discus the assumptions in simple and multiple regression, measure model adequacy in regression, residual analysis, multicollinearity, heteroskedasticity, nonnormality and nonlinearity, to select best regression model, to make variable selection and to give an introduction to nonlinear regression.

Learning Outcomes of the Course Unit

1	Simple Linear Regression and Correlation
2	Residual Analysis
3	Multiple Regression
4	Measures of Model Adequacy
5	Polynominal Regression
6	Problems in Multiple Regression
7	The Model Building Problem
8	Model Evaluation

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week	Subject	Description
1	Introduction to Statistics
2	Exploratory Data Analysis
3	Simple Linear Regression and Correlation
4	Interval Estimation in Simple Linear Regression
5	Residual Analysis
6	Multiple Regression
7	Confidence Intervals in Multiple Linear Regression
8	Measures of Model Adequacy
9	Polynominal Regression
10	Problems in Multiple Regression
11	The Model Building Problem-Stepwise Regression Methods
12	The Model Building Problem-All Possible Subsets Method
13	Model Evaluation
14	Project Presentation

Recomended or Required Reading

Textbook:
Kutner, M. H., Nachtsheim, C. J., Neter, J., & Li, W. (2005). Applied linear statistical models (Vol. 5). New York: McGraw-Hill Irwin.

Supplementary Book(s):
Draper, N. R., & Smith, H. (1998). Applied regression analysis (Vol. 326). John Wiley & Sons.

Mendenhall, W., Sincich, T., & Boudreau, N. S. (1996). A second course in statistics: regression analysis (Vol. 5). Upper Saddle River, NJ: Prentice Hall.

Planned Learning Activities and Teaching Methods

Lecture format, built around the textbook readings and computer applications with numerous examples chosen to illustrate theoretical concepts. Lots of drill with emphasis on practice. Questions are encouraged and discussion of material stressed.Lecture and problem solving.

Assessment Methods

SORTING NUMBER	SHORT CODE	LONG CODE	FORMULA
1	PRJ	PROJECT
2	MTE	MIDTERM EXAM
3	FIN	FINAL EXAM
4	FCG	FINAL COURSE GRADE	PRJ * 0.30 + MTE * 0.30 + FIN * 0.40
5	RST	RESIT
6	FCGR	FINAL COURSE GRADE (RESIT)	PRJ * 0.30 + MTE * 0.30 + RST * 0.40

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of exams and homeworks

Language of Instruction

English

Course Policies and Rules

It is necessary that attendance to the homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy.

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
Prof. Neslihan DEMIREL
e-mail: neslihan.ortabas@deu.edu.tr
Tel: 0232 301 86 00

Office Hours

Please send an e-mail for a meeting request.

Work Placement(s)

None

Workload Calculation

Activities	Number	Time (hours)	Total Work Load (hours)
Lectures	14	3	42
Preparations before/after weekly lectures	14	2	28
Preparation for midterm exam	1	30	30
Preparation for final exam	1	40	40
Project Preparation	1	30	30
Final	1	2	2
Midterm	1	2	2
TOTAL WORKLOAD (hours)			174

Contribution of Learning Outcomes to Programme Outcomes

PO/LO	PO.1	PO.2	PO.5	PO.6
LO.1	4	5	5	5
LO.2	4	5	5	5
LO.3	4	5	5	5
LO.4	4	5	5	5
LO.5	4	5	5	5
LO.6	4	5	5	5
LO.7	4	5	5	5
LO.8	4	5	5	5

COURSE UNIT TITLE

DEGREE PROGRAMMES

Description of Individual Course Units

Offered By

Level of Course Unit

Course Coordinator

Offered to

Course Objective

Learning Outcomes of the Course Unit

Mode of Delivery

Prerequisites and Co-requisites

Recomended Optional Programme Components

Course Contents

Recomended or Required Reading

Planned Learning Activities and Teaching Methods

Assessment Methods

Further Notes About Assessment Methods

Assessment Criteria

Language of Instruction

Course Policies and Rules

Contact Details for the Lecturer(s)

Office Hours

Work Placement(s)

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes

CONTACT INFORMATION