Ä°ST647 - ANALYSIS of CONTINGENCY TABLES
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| ANALYSIS of CONTINGENCY TABLES | Ä°ST647 | 1st Semester | 3 | 0 | 3 | 8 |
| Prequisites | None | |||||
| Course language | Turkish | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Discussion Problem Solving | |||||
| Instructor (s) | Assoc.Prof.Dr. Ayfer Ezgi Yılmaz | |||||
| Course objective | Categorical data analysis | |||||
| Learning outcomes |
| |||||
| Course Content | 1. Structure of contingency tables 2.Chi-square distribution and goodnes of fit statistics 3.Exact tests 4.Ä°nference for odds ratio. 5.Analysis of two way contingency tables 6. Analysis of multi way contingency tables 7. Loglinear models 8.Logit models | |||||
| References | 1. Agresti, A., 1984, Analysis of Ordinal Categorical Data, John Wiley and Sons, New York. 2. Agresti, A., 2002, Categorical Data Analysis, John Wiley and Sons, New York. 3. Aktaş Altunay, S., Yılmaz, A.E., Bahçecitapar, M., Bakacak Karabeli, 2021, SPSS ve R Uygulamalı Kategorik Veri Çözümlemesi, Seçkin Yayıncılık, Ankara. 4. Lawal, B., 2003, Categorical Data Analysis with SAS and SPSS Applications, New Jersey: Lawrence Erlbaum Associates, Publishers, Inc. 5. Saraçbaşı, T. and Aktaş Altunay, S., 2016, Kategorik Veri Çözümlemesi, Hacettepe Üniversitesi Yayınları, Ankara. 6. Shoukri, M.M., 2004, Measures of Interobserver Agreement, Florida: Chapman & Hall/CRC Press LLC. 7. Gwet, K.L., 2014, Handbook of Inter-rater Reliability, 4th Edition, Maryland: Advanced Analytics, LLC. | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Categorical data types and contingency tables |
| Week 2 | Chi-square distribution and goodness-of-fit statistics |
| Week 3 | Analysis of 2x2 contingency tables and odds ratio |
| Week 4 | Analysis of RxC tables and coefficients of association |
| Week 5 | Log-linear models |
| Week 6 | Mixed models for two dimensional contingency tables |
| Week 7 | Midterm Exam |
| Week 8 | Mixed models for higher dimensional contingency tables |
| Week 9 | Analysis of square contingency tables |
| Week 10 | Coefficients of Agreement |
| Week 11 | Agreement models |
| Week 12 | Binary logistic regression |
| Week 13 | Multinomial logistic regression |
| Week 14 | Ordered logistic regression |
| Week 15 | Presentations |
| Week 16 | Final exam |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 0 | 0 |
| Laboratory | 0 | 0 |
| Application | 0 | 0 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 2 | 10 |
| Presentation | 1 | 10 |
| Project | 1 | 10 |
| Seminar | 0 | 0 |
| Midterms | 1 | 20 |
| Final exam | 1 | 50 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 6 | 50 |
| Percentage of final exam contributing grade succes | 1 | 50 |
| Total | 100 | |
WORKLOAD AND ECTS CALCULATION
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 14 | 3 | 42 |
| Laboratory | 0 | 0 | 0 |
| Application | 14 | 2 | 28 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 14 | 6 | 84 |
| Presentation / Seminar Preparation | 1 | 16 | 16 |
| Project | 0 | 0 | 0 |
| Homework assignment | 2 | 10 | 20 |
| Midterms (Study duration) | 1 | 20 | 20 |
| Final Exam (Study duration) | 1 | 30 | 30 |
| Total Workload | 47 | 87 | 240 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. improves the undergraduade theoretical and applied knowlege | X | ||||
| 2. does researches with focusing on a specific area | X | ||||
| 3. offers new solutions to statistical problems | X | ||||
| 4. uses the profiency knowlegde gained in Statistics in interdiscipliner studies | X | ||||
| 5. presents a particular subject on Statistics in a certain time effectively | X | ||||
| 6. fullfilles new projects and events on Statistics. Has the ability of conducting, carrying out and reporting a project. | X | ||||
| 7. has the ability of scientific reasoning. | X | ||||
| 8. has the ability of analythic thinking | X | ||||
| 9. follows up the new developments on proficiency in both national and international area | X | ||||
| 10. follows the statistics literature. | X | ||||
| 11. uses the Information technologies in advance level | X | ||||
| 12. has capable of individual study and independent decision making | X | ||||
| 13. Has the necessary qualifications for team work and team leader | X | ||||
| 14. Improves a foreign language to follow the relevant literature and to present those studies | X | ||||
| 15. has the professional and ethical responsibility | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest