INTERNATIONAL BURCH UNIVERSITY
Faculty of Engineering and Natural Sciences
Department of Genetics and Bioengineering
20172018
SYLLABUS 
Code 
Name 
Level 
Year 
Semester 
GBE 202 
Biostatistics 
Undergraduate 
2 
Spring 
Status 
Number of ECTS Credits 
Class Hours Per Week 
Total Hours Per Semester 
Language 
Compulsory 
4 
2 + 2 
90 
English 
Biostatistics is essential to ensuring that findings and practices in public health and biomedicine are supported by reliable evidence. This course covers the basic tools for the collection, analysis, and presentation of data in all areas of public health. Central to these skills is assessing the impact of chance and
variability on the interpretation of research findings and subsequent recommendations for public health practice and policy. Topics covered include: general principles of study design; hypothesis testing; review of methods for comparison of discrete and continuous data including ANOVA, ttest, correlation, and
regression. 
COURSE OBJECTIVE 
Students who successfully complete this course will be able to:
•Describe the roles biostatistics serves in public health and biomedical research;
•Explain general principles of study design and its implications for valid inference when, for example, identifying risk factors for disease, isolating targets for prevention, and assessing the effectiveness of one or more interventions;
•Assess data sources and data quality for the purpose of selecting appropriate data for specific research questions;
•Translate research objectives into clear, testable statistical hypotheses;
•Describe basic principles and the practical importance of key concepts from probability and inference, inductive versus deductive reasoning, including random variation, systematic error, sampling error, measurement error, hypothesis testing, type I and type II errors, and confidence
bounds;
•Apply numerical, tabular, and graphical descriptive techniques commonly used to characterize and summarize public health data;
•Identify appropriate statistical methods to be applied in a given research setting, apply these methods, and acknowledge the limitations of those methods;
•Evaluate computer output containing statistical procedures and graphics and interpret it in a public health context; and
•
Differentiate between quantitative problems that can be addressed with standard, commonly used statistical methods and those requiring input from a professional biostatistician. 
COURSE CONTENT 
 Introduction to Introduction to Biostatistics
 Descriptive Statistics and Graphical Displays
 Data and Variables
 Mean, Median. Quartiles
 Standard Deviations and Outliers
 Correlations, Pearson Correlation
 Midterm Exam

 Regression
 Inference Statistics, Two way tables
 Normal Distirbutions
 Z score, ttest
 Probability
 Chisquare
 ANOVA test
 Final Exam

LABORATORY/PRACTICE PLAN 
 Introduction to Data
 Variables
 Filtering data
 Mean, Median. Quartiles calculations
 Standard deviation calculation
 Correlation calculations
 Midterm
 Regression questions
 Two tables comperison
 Z score calculation
 Drawing tables and normal distribution
 Probability
 Chisquare
 ANOVA
 Preparation for final

Description 
 Interactive Lectures
 Excersises
 Presentation
 Problem solving

Description (%) 
Midterm Exam(s)  1  30  Lab/Practical Exam(s)  1  20  Attendance  1  10  Final Exam  1  40 

Learning outcomes 
 Introduction to Introduction to Biostatistics
 Descriptive Statistics and Graphical Displays
 Data and Variables
 Mean, Median. Quartiles
 Standard Deviations and Outliers
 Correlations, Pearson Correlation
 Biostatistical problems and solutions

ECTS (Allocated based on student) WORKLOAD 
Lecture (14 weeks x Lecture hours per week)  14  2  28  Laboratory / Practice (14 weeks x Laboratory/Practice hours per week)  14  2  28  Midterm Examination (1 week)  1  2  2  Final Examination(1 week)  1  2  2  Preparation for Midterm Examination  1  10  10  Preparation for Final Examination  1  20  20  Assignment / Homework/ Project    0  Seminar / Presentation    0 

