BME3005 BiostatisticsBahçeşehir UniversityDegree Programs MECHATRONICS (TURKISH)General Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
MECHATRONICS (TURKISH)
Associate TR-NQF-HE: Level 5 QF-EHEA: Short Cycle EQF-LLL: Level 5

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
BME3005 Biostatistics Spring
Fall
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: Associate (Short 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 improve fundamental computer knowledge, to encourage students using office and package programs.
2) Ability to have and use of fundamental mathematics knowledge and skills the usage of relevant materials.
3) Ability to recognize general structures of machine equipments and the features of shaping
4) Ability to grasp manufacturing processes and cutting tool materials, materials, statics, mechanics and fluid science fundemantal knowledge.
5) Ability to draw assembly and auxilary devices as well as to draw whole or details of a system.
6) Ability to have a knowledge of fundemantal manufacturing process such as turning, milling, punching,grinding and welding techniques and to have a self esteem in order to work behind the bench.
7) Ability to do computer aided design and write program on digital benches.
8) Ability to prepare project report, follow up project process and implement projects.
9) ability to learn the areas of usage of electronic circuit components. Ability to grasp and write programs for micro controllers and for their components. Ability to design relevant circuits.
10) Ability to understand the electric motors principles and AC-DC analysis
11) Ability to gain a dominaion on visual programming
12) Having the ability to communicate efficiently in verbal and written Turkish, to know at least one foreign language in order to communicate with the colleagues and customers.