Description of Individual Course Units
Course Unit CodeCourse Unit TitleType of Course UnitYear of StudySemesterNumber of ECTS Credits
İST315CATEGORICAL DATA ANALYSISElective354
Level of Course Unit
First Cycle
Objectives of the Course
Defining and modeling of categorical data, applying of these models using statistical programs.
Name of Lecturer(s)
Dr. Öğr. Üyesi Özge ELMASTAŞ GÜLTEKİN
Learning Outcomes
1Facility in defining of categorical data.
2Understanding of logistic regression and log-linear models.
3Facility in the analysis of categorical data using statistical programs.
Mode of Delivery
Face to Face
Prerequisites and co-requisities
None
Recommended Optional Programme Components
None
Course Contents
Defining and classifying categorical data, modeling of categorical data, generating contingency tables, modeling of log-linear and logistic regression.
Weekly Detailed Course Contents
WeekTheoreticalPracticeLaboratory
1Basic Concepts
2Distributions for Categorical Data
3Estimation, Goodness of Fit Tests
4Contingency Tables
5Tests of Independence and Homogeneity
62×2 and i×j Contingency Tables
7Applying Contingency Tables using Statistical Programs
8General Revision
9Midterm
10Logistic Regression Model for Binary Response
11Logistic Regression Model for Multiple Response
12Applying Logistic Regression Models for Binary and Multiple Responses using Statistical Programs
13Log-linear Models for Two way Contingency Tables
14Log-linear Models for Three way Contingency Tables
15Model Selection and Interpretation
16General Revision
Recommended or Required Reading
1) Alan Agresti, 2002, “Categorical Data Analysis”, John Wiley&Sons. 2) Bayo Lawol, 2003, “Categorical Data Analysis with SAS and SPSS Applications”, Psychology Press.
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Term (or Year) Learning ActivitiesQuantityWeight
SUM0
End Of Term (or Year) Learning ActivitiesQuantityWeight
SUM0
SUM0
Language of Instruction
Turkish
Work Placement(s)
-
Workload Calculation
ActivitiesNumberTime (hours)Total Work Load (hours)
Midterm Examination122
Final Examination122
Attending Lectures14342
Practice236
Self Study12336
Individual Study for Homework Problems16232
TOTAL WORKLOAD (hours)120
Contribution of Learning Outcomes to Programme Outcomes
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LO154 4  4  4  45          
LO2554 5 4  5  45  45  5  5
LO35 5 545      555    5  5
* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High
 
Ege University, Bornova - İzmir / TURKEY • Phone: +90 232 311 10 10 • e-mail: intrec@mail.ege.edu.tr