| Course Description |
|
| Course Name |
: |
Categorical Data Analysis |
|
| Course Code |
: |
ISB-508 |
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| Course Type |
: |
Optional |
|
| Level of Course |
: |
Second Cycle |
|
| Year of Study |
: |
1 |
|
| Course Semester |
: |
Spring (16 Weeks) |
|
| ECTS |
: |
6 |
|
| Name of Lecturer(s) |
: |
Assoc.Prof.Dr. DENİZ ÜNAL
|
|
| Learning Outcomes of the Course |
: |
Know the basic definitions of the categorical data analysis.
Have the knowledge of Chi-square tests, log-likelihood ratio, contingency tables
Interpret the findings of logistic regression analysis
Have the ability to interpret the Probit regression model and the application of SPSS
|
|
| Mode of Delivery |
: |
Face-to-Face |
|
| Prerequisites and Co-Prerequisites |
: |
None |
|
| Recommended Optional Programme Components |
: |
None |
|
| Aim(s) of Course |
: |
To teach students how to define the Categorical Data, the three-way and higher dimensional contingency tables, correlation analysis, multidimensional tables, and log linear models. |
|
| Course Contents |
: |
The definitions of analysis of 2x2 contingency tables; three-way and higher dimensional contingency tables, correlation analysis; multidimensional tables; log linear models; logit and multinomial logit models; logistic regression analysis; analysis of rxr tables |
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| Language of Instruction |
: |
Turkish |
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| Work Place |
: |
Department seminar room |
|
|
Course Outline /Schedule (Weekly) Planned Learning Activities |
| Week | Subject | Student's Preliminary Work | Learning Activities and Teaching Methods |
|
1 |
Basic definitions |
Reading the related references |
Lecture & In-Class Activities |
|
2 |
contingency tables |
Reading the related references |
Lecture & In-Class Activities |
|
3 |
Analysis of 2x2 contingency tables |
Reading the related references |
Lecture & In-Class Activities |
|
4 |
Analysis of 2x2 contingency tables |
Reading the related references |
Lecture & In-Class Activities |
|
5 |
Analysis of three dim. contingency tables |
Reading the related references |
Lecture & In-Class Activities |
|
6 |
Three-way and higher dimensional contingency tables |
Reading the related references |
Lecture & In-Class Activities |
|
7 |
Three-way and higher dimensional contingency tables |
Reading the related references |
Lecture & In-Class Activities |
|
8 |
Mid-term Exam |
Reading the related references |
Lecture & In-Class Activities |
|
9 |
Correlation analysis |
Reading the related references |
Lecture & In-Class Activities |
|
10 |
Multidimensional tables |
Reading the related references |
Lecture & In-Class Activities |
|
11 |
Log linear models |
Reading the related references |
Lecture & In-Class Activities |
|
12 |
Logistic regression analysis |
Reading the related references |
Lecture & In-Class Activities |
|
13 |
Multinominal logit model |
Reading the related references |
Lecture & In-Class Activities |
|
14 |
Logit and multinomial logit models and probit regression analysis |
Reading the related references |
Lecture & In-Class Activities |
|
15 |
Analysis of rxr tables |
Reading the related references |
Lecture & In-Class Activities |
|
16/17 |
Final Exam |
Review for the exam |
Written exam |
|
|
|
Required Course Resources |
| Resource Type | Resource Name |
| Recommended Course Material(s) |
 An introduction to Categorical Data Analysis, A. Agresti, John Wiley&Sons, 1996
Linear Models in Statistics, Rencher, Alvin C., John Wiley&Sons, INC., New York, USA, 2010.
|
| |
| Required Course Material(s) | |
|
|
| Contribution of the Course to Key Learning Outcomes |
| # | Key Learning Outcome | Contribution* |
|
1 |
Possess advanced level of theoretical and applicable knowledge in the field of Probability and Statistics. |
0 |
|
2 |
Conduct scientific research on Mathematics, Probability and Statistics. |
2 |
|
3 |
Possess information, skills and competencies necessary to pursue a PhD degree in the field of Statistics. |
0 |
|
4 |
Possess comprehensive information on the analysis and modeling methods used in Statistics. |
4 |
|
5 |
Present the methods used in analysis and modeling in the field of Statistics. |
2 |
|
6 |
Discuss the problems in the field of Statistics. |
5 |
|
7 |
Implement innovative methods for resolving problems in the field of Statistics. |
5 |
|
8 |
Develop analytical modeling and experimental research designs to implement solutions. |
5 |
|
9 |
Gather data in order to complete a research. |
5 |
|
10 |
Develop approaches for solving complex problems by taking responsibility. |
5 |
|
11 |
Take responsibility with self-confidence. |
0 |
|
12 |
Have the awareness of new and emerging applications in the profession |
5 |
|
13 |
Present the results of their studies at national and international environments clearly in oral or written form. |
5 |
|
14 |
Oversee the scientific and ethical values during data collection, analysis, interpretation and announcment of the findings. |
5 |
|
15 |
Update his/her knowledge and skills in statistics and related fields continously |
4 |
|
16 |
Communicate effectively in oral and written form both in Turkish and English. |
2 |
|
17 |
Use hardware and software required for statistical applications. |
0 |
| * Contribution levels are between 0 (not) and 5 (maximum). |
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