BME3005 BiostatisticsBahçeşehir UniversityDegree Programs NEW MEDIAGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
NEW MEDIA
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
BME3005 Biostatistics Spring 2 2 3 6
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Non-Departmental Elective
Course Level: Bachelor’s Degree (First Cycle)
Mode of Delivery: Face to face
Course Coordinator : Dr. Öğr. Üyesi BURCU TUNÇ ÇAMLIBEL
Course Lecturer(s): Dr. Öğr. Üyesi BURCU TUNÇ ÇAMLIBEL
Recommended Optional Program Components: None
Course Objectives: - The course provides an introduction to selected important topics in biostatistical concepts and reasoning. This course represents an introduction to the field and provides a survey of data and data types. Specific topics include tools for describing central tendency and variability in data; methods for performing inference on population means and proportions via sample data; statistical hypothesis testing and its application to group comparisons; issues of power and sample size in study designs; and random sample and other study types; regression analysis, confidence intervals, correlations

Learning Outcomes

The students who have succeeded in this course;
- The students who have succeeded in this course;
I. Interpret statistical results correctly, effectively, and in context.
II. Select an appropriate test for comparing two or more populations, and interpret and explain a p-value
III. Understand the concept of the power of data.
IV. Calculate and interpret confidence intervals for population means and proportions
V. Understand regression analysis and correlation of variables.

Course Content

Design of Experiments, Statistical programming: , Exploratory Data Analysis and Descriptive Statistics, Probability Theory, Sampling Distributions and the Central Limit Theorem, Estimation, Statistical Inference, Contingency tables, Nonparametric Tests, Power and sample size, ANOVA, Correlation and Regression, Logistic regression, Survival Analysis, applications on biological datasets.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction to biostatistics
2) Descriptive Statistics
3) Probability Theory
4) Sampling Distributions and the Central Limit Theorem
5) ANOVA
6) The Special Case of Two Groups: the t test
7) Contingency tables, Chi Square Test, z-test
8) Fisher Exact Test, Relative Risk, Odds Ratio
9) Power and Sample size
10) Paired t-test, Repeated Measures of Analysis of Variance, McNemar's Test
11) Nonparametric Tests: Mann-Whitney Rank-Sum Test, Wilcoxon Signed-Rank Test
12) Nonparametric Tests: Kruskal-Wallis Test, Friedman Test
13) Confidence Intervals
14) Correlation and Regression

Sources

Course Notes / Textbooks: Primer of Biostatistics, Stanton A. Glantz, McGraw-Hill, 7th Edition
Fundamental of Biostatistics, Bernard Rosner, Cengage Learning, 8th Edition
References:

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Quizzes 5 % 30
Midterms 1 % 30
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 60
PERCENTAGE OF FINAL WORK % 40
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Study Hours Out of Class 14 7 98
Quizzes 5 1 5
Midterms 1 3 3
Final 1 3 3
Total Workload 151

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) To be able to critically interpret and discuss the theories, the concepts, the traditions, and the developments in the history of thought which are fundamental for the field of new media, journalism and communication.
2) To be able to attain written, oral and visual knowledge about technical equipment and software used in the process of news and the content production in new media, and to be able to acquire effective abilities to use them on a professional level.
3) To be able to get information about the institutional agents and generally about the sector operating in the field of new media, journalism and communication, and to be able to critically evaluate them.
4) To be able to comprehend the reactions of the readers, the listeners, the audiences and the users to the changing roles of media environments, and to be able to provide and circulate an original contents for them and to predict future trends.
5) To be able to apprehend the basic theories, the concepts and the thoughts related to neighbouring fields of new media and journalism in a critical manner.
6) To be able to grasp global and technological changes in the field of communication, and the relations due to with their effects on the local agents.
7) To be able to develop skills on gathering necessary data by using scientific methods, analyzing and circulating them in order to produce content.
8) To be able to develop acquired knowledge, skills and competence upon social aims by being legally and ethically responsible for a lifetime, and to be able to use them in order to provide social benefit.
9) To be able to operate collaborative projects with national/international colleagues in the field of new media, journalism and communication.
10) To be able to improve skills on creating works in various formats and which are qualified to be published on the prestigious national and international channels.