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Syllabus ( BSB 615 )


   Basic information
Course title: Biostatistics
Course code: BSB 615
Lecturer: Dr. Öğr. Üyesi Pınar PİR
ECTS credits: 7.5
GTU credits: 3 (3+0+0)
Year, Semester: 1, Fall
Level of course: Second Cycle (Master's)
Type of course: Compulsory
Language of instruction: English
Mode of delivery: Face to face
Pre- and co-requisites: None
Professional practice: No
Purpose of the course:
   Learning outcomes Up

Upon successful completion of this course, students will be able to:

  1. Have a thorough understanding of fundamentals probability and statistics

    Contribution to Program Outcomes

    1. Define and manipulate basic and advanced concepts in the field of Bioinformatics and Systems Biology
    2. Grasp the importance of bioinformatics and systems biology based viewpoint in the analysis and interpretation of working principles of the cell.

    Method of assessment

    1. Written exam
    2. Homework assignment
  2. Have an understanding of types of hypothesis testing and applications in life sciences

    Contribution to Program Outcomes

    1. Define and manipulate basic and advanced concepts in the field of Bioinformatics and Systems Biology
    2. Link the concepts belonging to the different disciplines and interpret & analyze scientific research in these disciplines.
    3. Acquire scientific knowledge and work independently
    4. Grasp the importance of bioinformatics and systems biology based viewpoint in the analysis and interpretation of working principles of the cell.

    Method of assessment

    1. Written exam
    2. Homework assignment
  3. Equipped with biostatistics tools essential to bioinformatics and systems biology.

    Contribution to Program Outcomes

    1. Define and manipulate basic and advanced concepts in the field of Bioinformatics and Systems Biology
    2. Process and analyze genome-scale biological data using statistical methods and data mining methods.
    3. Link the concepts belonging to the different disciplines and interpret & analyze scientific research in these disciplines.
    4. Acquire scientific knowledge and work independently
    5. Find out new methods to improve his/her knowledge.

    Method of assessment

    1. Written exam
    2. Homework assignment
  4. Aware of biased uses of biostatistics in the literature

    Contribution to Program Outcomes

    1. Define and manipulate basic and advanced concepts in the field of Bioinformatics and Systems Biology
    2. Review the literature critically pertaining to his/her research projects, and connect the earlier literature to his/her own results.
    3. Acquire scientific knowledge and work independently
    4. Find out new methods to improve his/her knowledge.
    5. Demonstrating professional and ethical responsibility.

    Method of assessment

    1. Written exam
   Contents Up
Week 1: Descriptive Statistics: Presenting the data from patients
Week 2: Introduction to Probability: Understanding risks of disease
Homework 1 - Quiz 1
Week 3: Discrete Probability Distributions
Homework 2 - Quiz 2
Week 4: Continuous Probability Distributions: Design of clinical trials
Homework 3 - Quiz 3
Week 5: Estimation Methods
Homework 4 - Quiz 4
Week 6: Midterm Exam 1
Hypothesis Testing: One-Sample Inference - Identifying the Differentially Transcribed Genes
Homework 5 - Quiz 5
Week 7: Hypothesis Testing: Two-Sample Inference - Identifying the Differentially Transcribed Genes with Paired Data
Homework 6 - Quiz 6
Week 8: Nonparametric Methods: Analysis of Omics Data With Unknown Distribution
Homework 7 - Quiz 7
Week 9: Hypothesis Testing: Categorical Data
Homework 8 - Quiz 8
Week 10: Regression and Correlation Methods: Analysing the correlation between protein and gene expression levels
Homework 9 - Quiz 9
Week 11: Multisample Inference: ANOVA
Homework 10 - Quiz 10
Week 12: Midterm Exam 2
Experimental Design and Analysis Techniques
Homework 11 - Quiz 11
Week 13: Hypothesis Testing: Time-Dependant Data
Homework 12 - Quiz 12
Week 14: Case Study 1: Biased use of biostatistics in literature - How not to use p-value
Week 15*: Case Study 2: Biased use of biostatistics in journals/magazines
Week 16*: Final Exam
Textbooks and materials: B. Rosner, "Fundamentals of Biostatistics", Brooks/Cole, Boston, 2010
Recommended readings: RE. Walpole, RH. Myers, SL. Myers, K. Ye, "Probability and Statistics for Engineers and Scientists", Prentice Hall, Boston, 2012.
  * Between 15th and 16th weeks is there a free week for students to prepare for final exam.
Assessment Up
Method of assessment Week number Weight (%)
Mid-terms: 6 and 12 30
Other in-term studies: 0
Project: 0
Homework: 2-13 20
Quiz: 2-13 20
Final exam: 16 30
  Total weight:
(%)
   Workload Up
Activity Duration (Hours per week) Total number of weeks Total hours in term
Courses (Face-to-face teaching): 3 15
Own studies outside class: 4 16
Practice, Recitation: 0 0
Homework: 3 12
Term project: 0 0
Term project presentation: 0 0
Quiz: 0.5 12
Own study for mid-term exam: 10 2
Mid-term: 2 2
Personal studies for final exam: 10 1
Final exam: 3 1
    Total workload:
    Total ECTS credits:
*
  * ECTS credit is calculated by dividing total workload by 25.
(1 ECTS = 25 work hours)
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