| EUROPEAN UNION RELATIONS | |||||
| 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 be able to examine, interpret data and assess ideas with the scientific methods in the area of EU studies. | 2 |
| 2) | To be able to inform authorities and institutions in the area of EU studies, to be able to transfer ideas and proposals supported by quantitative and qualitative data about the problems. | 2 |
| 3) | To be introduced to and to get involved in other disciplines that EU studies are strongly related with (political science, international relations, law, economics, sociology, etc.) and to be able to conduct multi-disciplinary research and analysis on European politics. | 3 |
| 4) | To be able to evaluate current news on European Union and Turkey-EU relations and identify, analyze current issues relating to the EU’s politics and policies. | 2 |
| 5) | To be able to use English in written and oral communication in general and in the field of EU studies in particular. | 1 |
| 6) | To have ethical, social and scientific values throughout the processes of collecting, interpreting, disseminating and implementing data related to EU studies. | 1 |
| 7) | To be able to assess the historical development, functioning of the institutions and decision-making system and common policies of the European Union throughout its economic and political integration in a supranational framework. | 2 |
| 8) | To be able to evaluate the current legal, financial and institutional changes that the EU is going through. | 2 |
| 9) | To explain the dynamics of enlargement processes of the EU by identifying the main actors and institutions involved and compare previous enlargement processes and accession process of Turkey. | 2 |
| 10) | To be able to analyze the influence of the EU on political, social and economic system of Turkey. | 2 |
| 11) | To acquire insight in EU project culture and to build up project preparation skills in line with EU format and develop the ability to work in groups and cooperate with peers. | 2 |
| 12) | To be able to recognize theories and concepts used by the discipline of international relations and relate them to the historical development of the EU as a unique post-War political project. | 3 |