ELECTRICAL AND ELECTRONICS ENGINEERING | |||||
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 | Spring 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) | Adequate knowledge in mathematics, science and electric-electronic engineering subjects; ability to use theoretical and applied information in these areas to model and solve engineering problems. | |
2) | Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | |
3) | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues, according to the nature of the design.) | |
4) | Ability to devise, select, and use modern techniques and tools needed for electrical-electronic engineering practice; ability to employ information technologies effectively. | |
5) | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating engineering problems. | |
6) | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | |
7) | Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing. | |
8) | Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | |
9) | Awareness of professional and ethical responsibility. | |
10) | Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development. | |
11) | Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions. |