BÄ°S735 - BIOSTATISTICS
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| BIOSTATISTICS | BÄ°S735 | 1st Semester | 3 | 0 | 3 | 7 |
| Prequisites | None | |||||
| Course language | Turkish | |||||
| Course type | Must | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Discussion | |||||
| Instructor (s) | PROF. ERDEM KARABULUT, PhD - PROF. PINAR ÖZDEMİR, PhD - ASSOC. PROF. Osman DAĞ, PhD | |||||
| Course objective | Teaching basic statistics and biostatistics knowledge, to provide evaluating the studies from their own field about biostatistics. | |||||
| Learning outcomes |
| |||||
| Course Content | Basic statistical definitions, descriptive statistics of data set, theoretical distributions, sampling distributions, basic research designs, basic sampling methods, hypothesis tests, measures of association, regression analysis, definition and calculation of the risk measures, confidence intervals of the risk measures, statistical methods for rates. | |||||
| References | Daniel, Wayne W. 0471525146 Biostatistics : a foundation for analysis in the health sciences John Wiley and Sons New York 1991 | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Introduction, Descriptive and Inferential Statistics, Difference between Statistics and Biostatistics |
| Week 2 | Descriptive Statistics |
| Week 3 | Tables and graphics |
| Week 4 | Theoretical Distributions (Normal, Binomial and Poisson Distributions) |
| Week 5 | Sampling and Sampling distributions, standard error |
| Week 6 | Midterm exam |
| Week 7 | Introduction to hypothesis tests, Single Sample Tests |
| Week 8 | Two sample hypothesis tests |
| Week 9 | Hypothesis tests for more than two sample |
| Week 10 | Practice with Article Discussions |
| Week 11 | Midterm exam |
| Week 12 | Regression and correlation |
| Week 13 | Diagnostic tests measures of event-frequency |
| Week 14 | Advanced Topics in Biostatistics: (Logistic Regression and Cox 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 | 2 | 10 |
| Presentation | 0 | 0 |
| Project | 0 | 0 |
| Seminar | 0 | 0 |
| Midterms | 2 | 40 |
| Final exam | 1 | 50 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 4 | 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 | 6 | 84 |
| Presentation / Seminar Preparation | 1 | 6 | 6 |
| Project | 0 | 0 | 0 |
| Homework assignment | 2 | 9 | 18 |
| Midterms (Study duration) | 2 | 15 | 30 |
| Final Exam (Study duration) | 1 | 30 | 30 |
| Total Workload | 34 | 69 | 210 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. Graduates have knowledge related to the biophysical principles underlying all processes of life at the level of cell/tissue/organ/system | |||||
| 2. Has an ability use his/her higher intellectual processes such as critical thinking, problem solving decision development during his/her education period | |||||
| 3. Can take part in some research activities to contribute to the solution of a problem in the field of biophysics | |||||
| 4. Awaring of the fact that biophysics is a multidisciplinary field, follows the developments in other branches of the Medical&Basic Sciences | X | ||||
| 5. Can use computer software and laboratory equipment to produce appropriate stimulus, acquire the biological signals under the ideal conditions, quantitatively analyse the raw data | X | ||||
| 6. Acquired knowledge at an expertise level in statistical methods. Can choose the most suitable method for his/her research | X | ||||
| 7. Is aware of the importance of the ethical rules and regulations and perform laboratory research as defined by the GLP, Bio-Safety principles | |||||
| 8. Has the capacity of successfully preparing and presenting the report of the research work he/she takes part in, publishing at least one manuscript | |||||
| 9. Follows the activities of the national&international organizations related to his/her expertise and takes part in them | |||||
| 10. Shares the knowledge he/she acquired from biophysics with partners from all parts of the society; contributes to the formation of the knowledge-based society | |||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest