GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
CATEGORICAL DATA ANALYSIS/İST-425
Course Title: CATEGORICAL DATA ANALYSIS
Credits 3 ECTS 5
Semester 7 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  TURKISH
 -- NAME OF LECTURER(S)
  Yrd.Doç.Dr.Meltem Ekiz
 -- WEB SITE(S) OF LECTURER(S)
  http://websitem.gazi.edu.tr/site/mekiz
 -- EMAIL(S) OF LECTURER(S)
  ozmeltem@gazi.edu.tr
 -- LEARNING OUTCOMES OF THE COURSE UNIT
Learn to define and classify categorical variables
Learn the statistical analysis methods, in case of categorical variables
Learn to built models for the data
Learn to obtain the results by using SPSS.
 -- MODE OF DELIVERY
  The mode of delivery is face to face
 -- PREREQUISITES AND CO-REQUISITES
  There is no prerequisite or co-requisite for this course
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
  There is no recommended optional programme component for this course
 --COURSE CONTENT
1. Week  Fundamental concepts
2. Week  Univariate analysis, Binomial and multinomial distribution, Poisson distribution
3. Week  Estimation, goodness of fit tests
4. Week  Sample size and zeros, model test
5. Week  Contingency tables
6. Week  Chi-squared tests of independence
7. Week  2×2 tables, I×2 tables, I×J contingency tables
8. Week  Mid-term Exam
9. Week  Exact inference for small samples, Fisher's exact test
10. Week  Three way tables, marginal and conditional odds ratio and independence
11. Week  Log-linear model in contingency tables
12. Week  Log-linear model for three way tables
13. Week  Model selection, summarize and interpret the analysis
14. Week  Logit analysis, model selection, summarize and interpret the analysis
15. Week  Correspondence analysis, summarize and interpret the analysis
16. Week  Final exam
 -- RECOMMENDED OR REQUIRED READING
  Agresti, A., 1990, Categorical Data Analysis, John Wiley&Sons. Azen, R. And Walker, C.M., 2011, Categorical Data Analysis for the Behavioral and Social Sciences, Taylor&Francis Group, LLC. Freeman, D. H., 1987, AppliedCategorical Data Analysis, MarcelDekker. Lawal, B., 2003, Categorical Data Analysis with SAS and SPSS Applications, Lawrence Erlbaum Associates, Inc.
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Lecture.
 -- WORK PLACEMENT(S)
  No
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
1
30
 Assignment
3
10
 Exercises
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Contribution of In-term Studies to Overall Grade  
40
 Contribution of Final Examination to Overall Grade  
60
 -- WORKLOAD
 Efficiency  Total Week Count  Weekly Duration (in hour)  Total Workload in Semester
 Theoretical Study Hours of Course Per Week
14
3
42
 Practising Hours of Course Per Week
0
 Reading
14
2
28
 Searching in Internet and Library
14
2
28
 Designing and Applying Materials
0
 Preparing Reports
3
3
9
 Preparing Presentation
0
 Presentation
0
 Mid-Term and Studying for Mid-Term
1
8
8
 Final and Studying for Final
2
8
16
 Other
0
 TOTAL WORKLOAD: 
131
 TOTAL WORKLOAD / 25: 
5.24
 ECTS: 
5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
11. The statistical textbooks which include latest information about statistics, equipment and other resources supported by scientific approach on undergraduate level have theoretical and practical knowledge.X
22. Statisticians by using knowledge and skills acquired at bachelor degree level model, analyze, and interpret datasets.X
33. Statisticians identify and analyze the problems with current developments in statistic and also develop solutions based upon researches and proofs.
44. Statisticians apply theoretical and practical knowledge acquired in Statistics at bachelor degree level to the current problems.X
55. Statisticians have the ability to use computer software and computing technology at the certain level required by statistics field.X
66. Statisticians take responsibility at disciplinary and interdisciplinary studies as an individual or a team member.
77. Statisticians must have knowledge and ability to follow development in the field of Statistics, and must develop life long-learning attitudes.X
88. By using a foreign language, statistician can keep track of every statistical information, and communicate with colleagues.
99. Applying the statistical knowledge in the professional sense, statistician has social, scientific, and ethical values.
1010. A statistician must have the ability to social sensitivity and socialization.
1111. During the process of inference, a statistician uses time efficiently with the analytical thinking ability.