BÄ°S608 - ADVANCED BIOSTATISTICAL ANALYSIS
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| ADVANCED BIOSTATISTICAL ANALYSIS | BÄ°S608 | 2nd Semester | 3 | 0 | 3 | 6 |
| Prequisites | Having successfully completed the lectures BIS 605 or BIS 735 | |||||
| Course language | Turkish | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Discussion | |||||
| Instructor (s) | PROF. ERDEM KARABULUT, PHD - PROF. PINAR ÖZDEMİR, PHD | |||||
| Course objective | To teach the advanced biostatistical methods in addition to the basics of biostatistics. | |||||
| Learning outcomes |
| |||||
| Course Content | 1. Descriptive statistics: Central tendency, measures of location and dispersion, 2. Measures of risk and hypothesis tests regarding these measures, 3. Sample size, 4. Life tables, calculating expected lifetime, 5. Logistic, probit, Poisson and Cox proportional hazard regression. | |||||
| References | 1. Lachin J.M., Biostatistical methods, John WiÅŸley & Sons Inc. 2000 2. Dowson B., Biostatistics, Lange Medical Books/McGraw Hill, 2001 3. Woolson R.F., Statistical Methods For The Analysis Of Biomedical Data, John Wiley & Sons Inc. 1987 | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Descriptive statistics: Central tendency, measures of location and dispersion |
| Week 2 | Measures of Risk |
| Week 3 | Statistical Distributions |
| Week 4 | Overview of Hypothesis Tests |
| Week 5 | Hypothesis tests related to descriptive statistics and measures of risk |
| Week 6 | Calculating required sample size |
| Week 7 | Building Lifetables and calculating expected lifetime |
| Week 8 | Basic estimation methods used in survival analysis |
| Week 9 | Midterm exam |
| Week 10 | Overview of regression and correlation |
| Week 11 | Logistic Regression |
| Week 12 | Probit Regression |
| Week 13 | Poisson Regression and Negative Binomial Regression |
| Week 14 | Cox Proportional Hazard Regression |
| Week 15 | Preparation to final exam |
| 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 | 3 | 10 |
| Presentation | 1 | 15 |
| Project | 0 | 0 |
| Seminar | 0 | 0 |
| Midterms | 1 | 25 |
| Final exam | 1 | 50 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 5 | 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 | 0 | 0 | 0 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 14 | 2 | 28 |
| Presentation / Seminar Preparation | 1 | 20 | 20 |
| Project | 0 | 0 | 0 |
| Homework assignment | 3 | 15 | 45 |
| Midterms (Study duration) | 1 | 15 | 15 |
| Final Exam (Study duration) | 1 | 30 | 30 |
| Total Workload | 34 | 85 | 180 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. A specialist with a graduate diploma in biostatistics: Has the knowledge to lead research planning, execution, and finalization, staying updated on literature and current studies. | X | ||||
| 2. Critically evaluates studies and scientific papers in presentations, courses, seminars, and conferences, encouraging a critical perspective. | X | ||||
| 3. Has the sufficient theoretical and practical knowledge of statistics to determine the appropriate statistical analysis and to grasp the results correctly. | X | ||||
| 4. Be proficient in computer use and statistical software, ensuring data suitability and recommending solutions for data management and analysis methods. | X | ||||
| 5. Effectively communicates analysis issues through active participation in discussions, exchanging information with the advisor, and presenting seminars. | X | ||||
| 6. Provides method suggestions in consultancy, does research planning, prepares research reports. | X | ||||
| 7. Maintains scientific accuracy and ethical values, remaining careful against any conscious or unconscious biases throughout the study. | X | ||||
| 8. Supports a counseling service under faculty supervision, may handle independent projects, and participates in conferences, presenting papers or posters with the academic advisor. | X | ||||
| 9. Be ready for multidisciplinary studies, collaborating professionally in group settings and gains the ability to assign individuals in the group. | X | ||||
| 10. Integrates diverse disciplines to analyze and synthesize information, offering solutions. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest