Iğdır University Lifelong Learning Programme

Description of Individual Course Units

Course Unit Code	Course Unit Title	Type of Course Unit	Year of Study	Semester	Number of ECTS Credits
ZOO-23-121		Elective	1	2	6

Level of Course Unit

Second Cycle

Objectives of the Course

Aim of the course is to build the best mathematical model that explains relations among dependent and independent variables and estimate structural analysis by using the model mentioned.

Name of Lecturer(s)

Doç. Dr. Cem Tırınk

Learning Outcomes

1	Research of the relationship between variables
2	Building the modeling based on the variables
3	Estimating and analyzing regression models

Mode of Delivery

Daytime Class

Prerequisites and co-requisities

None

Recommended Optional Programme Components

None

Course Contents

Relationship between variables, analysis of correlation, simple linear regression, confidences of the regression models, nonlinear regression, Assumptions of Multiple regression models and diversions from these assumptions

Weekly Detailed Course Contents

Week	Theoretical	Practice	Laboratory
1	Introduction to Regression analysis, Definitions and goals of Regression Analysis, type of data for Regression
2	Simple Linear Regression, Ordinary Least Square Methods for Regression Parameter Estimation
3	Introducing the SPSS package program
4	Standard Error of Regression Models and Regression Coefficients. Correlation and Determination Coefficients and Significance Tests	Application with SPSS package program
5	Multiple Regression Models and Their Assumptions, Least-squares estimation of Multiple regression coefficients	Application with SPSS package program
6	Confidence intervals for regression coefficients, coefficient of elasticity	Application with SPSS package program
7	Multiple determination coefficient, Analysis of variance for validity of regression model	Application with SPSS package program
8	Midterm exam
9	Simple and multiple nonlinear regression models. The assumptions of multiple regression models, Investigate of the normality for the error term	Application with SPSS package program
10	Determining the Autocorrelation problems and solution methods	Application with SPSS package program
11	Assumption of Homoscedasticity, Heteroscedasticity problems and solution methods	Application with SPSS package program
12	Problem of Multicollinearity and solution methods	Application with SPSS package program
13	Alternative methods for selecting variables for the multiple linear regression models	Application with SPSS package program
14	Statistical package programs application for solution the regression models	SPSS package program applications

Recommended or Required Reading

1-Draper, N, R., Smith, H., éApplied Regression Analysis”, John Wiley&Sons, 1998 2-Orhunbilge, N.,“Uygulamalı Regresyon ve Korelasyon Analizi”, Ataol yayınları,İstanbul, 1996. 3-Gujarati, D, N., “Temel Ekonometri”, (Çeviren, Ümit Şenesen, Gülay Günlük Şenesen), Literatür yayınları, 1999 4-Fox, C., “Applied Regression Analysis, Linear Models, and Related Methods”, Sage Publication, 1997

Planned Learning Activities and Teaching Methods

Assessment Methods and Criteria

Term (or Year) Learning Activities	Quantity	Weight
Midterm Examination	1	100
SUM		100
End Of Term (or Year) Learning Activities	Quantity	Weight
Final Examination	1	100
SUM		100
Term (or Year) Learning Activities		40
End Of Term (or Year) Learning Activities		60
SUM		100

Language of Instruction

Turkish

Work Placement(s)

None

Workload Calculation

Activities	Number	Time (hours)	Total Work Load (hours)
Midterm Examination	1	2	2
Final Examination	1	2	2
Attending Lectures	14	3	42
Individual Study for Mid term Examination	1	35	35
Individual Study for Final Examination	1	55	55
Reading	14	3	42
TOTAL WORKLOAD (hours)			178

Contribution of Learning Outcomes to Programme Outcomes

	PO 1	PO 2	PO 3	PO 4	PO 5	PO 6
LO1	3	4	4	5	4	4
LO2	4	4	4	4	5	5
LO3	5	5	5	5	5	5

* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High