GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
ADVANCED METHODS IN BIOSTATISTICS/5151303
Course Title: ADVANCED METHODS IN BIOSTATISTICS
Credits 3 ECTS 7.5
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
Grasping the research designs used in the health sciences depending on the information learned in the field.
Grasping the biostatistics disciplinary interaction related to his field.
Understanding study design in health sciences
Able to power analysis and sample size
Understanding risk measurements in health sciences
Understanding NNT, NNH, ITT
able to carry out and interpret interobserver agreement
Understanding Evidence-based medicine
Understanding randomization and randomized controlled trials
Understanding Cochran Systematic Review and able to reading literature in health sciences
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE
1. Week  Basic concepts of biostatistics.
2. Week  Summarizing and presentation data in health sciences
3. Week  Study designs in health sciences
4. Week  Study designs in health sciences
5. Week  Statistical power analysis in clinical research
6. Week  Sample size in clinical research
7. Week  Risk measures in health sciences
8. Week  Vital statistics
9. Week  Midterm exam
10. Week  NNT (Number Needed to Treat), NNH (Number Needed to Harm), ITT (Intention to Treat)
11. Week  Evaluation of inter-observer agreement
12. Week  Evidence-based medicine
13. Week  Randomization and randomized controlled trials
14. Week  Cochran systematic reviews
15. Week  Final exam
16. Week  ------------------------------
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
20
 Assignment
1
10
 Application
0
0
 Projects
0
0
 Practice
1
10
 Quiz
0
0
 Percent of In-term Studies  
40
 Percentage of Final Exam to Total Score  
60
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
0
0
 Reading Tasks
14
3
42
 Searching in Internet and Library
6
3
18
 Material Design and Implementation
6
3
18
 Report Preparing
4
3
12
 Preparing a Presentation
4
3
12
 Presentation
2
3
6
 Midterm Exam and Preperation for Midterm Exam
3
4
12
 Final Exam and Preperation for Final Exam
3
6
18
 Other (should be emphasized)
2
4
8
 TOTAL WORKLOAD: 
188
 TOTAL WORKLOAD / 25: 
7.52
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
11. Based on the capabilities of undergraduate level, the students enrolled to the program can develop and deepen their knowledge and skill at the level of expertise on the same field of the undergradute study or a different field.X
22. The students use their theoretical and practical knowledge at the level of expertise in the area of statistics.X
33. The students should evaluate their acquired knowledge and skills in a critical perspective and the critical point of view guides their learning process.X
44. Theoretical and practical knowledge gained in graduate level in the field of Statistics should be applied and transfer to the current problems.X
55. By performing the process from the identification of the scientific research problem to reporting and the process should be transferred in oral, written and visual ways.X
66. The students should use computer software and information technologies on the level required by the field of Statistics.X
77. The students should have the ability to use Statistics in interdisciplinary studies.X
88. The students should have enough foreign language level to pursue statistical literature.X
99. At the required level of field of statistics, he/she should use statistical software and information technology efficiently in a such a way that helps solving problems in his/her research.X
1010. In the process of applying knowledge in a professional sense, social, scientific, and ethical values should be regarded.X
 -- NAME OF LECTURER(S)
   (Prof. Dr. Bülent ÇELİK)
 -- WEB SITE(S) OF LECTURER(S)
   (https://abs.gazi.edu.tr/bucelik)
 -- EMAIL(S) OF LECTURER(S)
   (bucelik@gazi.edu.tr)