| 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 |
| EEE5022 | Applied Statistics | Fall | 3 | 0 | 3 | 9 |
| 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 : | Assoc. Prof. SAEID KARAMZADEH |
| Course Lecturer(s): |
Prof. Dr. SELİM ZAİM |
| Recommended Optional Program Components: | none.......... |
| Course Objectives: | The course introduces fundamental topics in statistics and implements its applications to industrial, medical, financial, energy and similar type very large-size datasets to infer meaninful statistical results. The course is for gradute students with no significant background on this subject. Implementations will be performed on the open source statistical software R. Introduction to R programming will be given. |
|
The students who have succeeded in this course; I. Identify basic terms in statistics. II. Gain ability to use and apply basic methods and programming tools used in statistics over various engineering disciplines. III. Ability to explore data and its relationships. IV. Ability to perform hypothesis testing for statistical problems. V. Perform statistical inference over statistical data. |
| Topics include: Introduction to R programming, Sampling, Data Exploration, Exploring Relationships, Probability, Random Variables and Probability Distributions, Estimation, Hypothesis Testing, Statistical Inference, Multiple Testing Correction, ANOVA, Analysis of Categorical Variables, Regression Analysis, Bayesian Analysis, Survival Analysis, Over Representation Analysis, Meta Analysis. |
| Week | Subject | Related Preparation |
| 1) | Introduction | |
| 2) | Introduction to R statistical programming | |
| 3) | Term Project | |
| 4) | Data Exploration with R | |
| 5) | Visualizing and Summarizing Relationships | |
| 6) | Probability and Random Variables | |
| 7) | Estimation in datasets | |
| 8) | Hypothesis Testing for various engineering applications | |
| 9) | Statistical Inference over various large datasets | |
| 10) | ANOVA | |
| 11) | Analysis of Categorical Variables | |
| 12) | Regression and Bayesian Analysis | |
| 13) | Survival analysis | |
| 14) | Over Representation Analysis |
| Course Notes / Textbooks: | Principles of Applied Statistics (Paperback), by D. R. Cox, Christl A. Donnelly 2011 ISBN-10: 1107644453 | ISBN-13: 978-1107644458 |
| References: | Introductory Statistics with R Peter Dalgaard 2011 ISBN 978-0-387-79053-4 |
| Semester Requirements | Number of Activities | Level of Contribution |
| Project | 1 | % 30 |
| Midterms | 1 | % 30 |
| Final | 1 | % 40 |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 30 | |
| PERCENTAGE OF FINAL WORK | % 70 | |
| Total | % 100 | |
| Activities | Number of Activities | Workload |
| Course Hours | 14 | 42 |
| Study Hours Out of Class | 14 | 42 |
| Project | 1 | 30 |
| Midterms | 1 | 40 |
| Final | 1 | 50 |
| Total Workload | 204 | |
| 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 |