LOGISTIC MANAGEMENT | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
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. |
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 |
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. |
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. |
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 |
Course Notes / Textbooks: | Primer of Biostatistics, Stanton A. Glantz, McGraw-Hill, 7th Edition Fundamental of Biostatistics, Bernard Rosner, Cengage Learning, 8th Edition |
References: |
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 |
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 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | To correctly identify the problems and to be able to ask the correct questions | |
2) | To have the ability for problem solving and to utilize analytical approach in dealing with the problems | |
3) | To be able to identify business processes and use them to increase the productivity in logistics system. | |
4) | To be fully prepared for a graduate study | 2 |
5) | Awareness of the new advancements in Information and Communications Technologies (ICT) and to be able to use them in logistics management effectively. internet and the electronic world | |
6) | To understand the components of logistics as well as the importance of the coordination among these components. | |
7) | To know the necessary ingredients for improving the productivity in business life | |
8) | To think innovatively and creatively in complex situations | 4 |
9) | To act and think both regionally and internationally | |
10) | To understand the demands and particular questions of globalization | |
11) | Aware of the two way interaction between globalization and logistics; as well as to use this interaction for increasing the productivity. | |
12) | To be able to use at least one foreign language both for communication and academic purposes | 2 |
13) | To acquire leadership qualities but also to know how to be a team member | |
14) | To understand the importance of business ethics and to apply business ethics as a principal guide in both business and academic environment |