COMPUTER ENGINEERING (ENGLISH, PHD) | |||||
PhD | TR-NQF-HE: Level 8 | QF-EHEA: Third Cycle | EQF-LLL: Level 8 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
ENM5203 | Statistical Data Analysis and Decision Making | Fall | 3 | 0 | 3 | 12 |
The course opens with the approval of the Department at the beginning of each semester |
Language of instruction: | En |
Type of course: | Departmental Elective |
Course Level: | |
Mode of Delivery: | Face to face |
Course Coordinator : | Dr. Öğr. Üyesi ETHEM ÇANAKOĞLU |
Course Lecturer(s): |
Prof. Dr. SELİM ZAİM Dr. Öğr. Üyesi YÜCEL BATU SALMAN |
Course Objectives: | This course provides the use of statistical and quantitative methods using computer technology to examine and explore data. It aims to build and interpret models from this data for decision making in all functional areas. |
The students who have succeeded in this course; Ability to make decisions with statistical methods, ability to collect meaningful data, ability to interpret data and transform it into information/knowledge |
Methods covered include: collecting data, summarizing and exploring data, hypothesis testing, confidence intervals, regression analysis, ANOVA. |
Week | Subject | Related Preparation | |
1) | Introduction: Description of data | ||
2) | Data collection | ||
3) | Descriptive Statistics | ||
4) | Confidence intervals | ||
5) | Hypothesis testing | ||
6) | Hypothesis testing | ||
7) | Midterm | ||
8) | Regression analysis | ||
9) | Regression analysis | ||
10) | ANOVA | ||
12) | ANOVA | ||
12) | SPSS | ||
13) | Project presentations | ||
14) | Project presentations |
Course Notes: | N/A |
References: | Statistics for Business: Decision Making and Analysis, Robert A. Stine, Dean Foster, Pearson, 2011, 0321123913 |
Semester Requirements | Number of Activities | Level of Contribution |
Attendance | % 0 | |
Laboratory | % 0 | |
Application | % 0 | |
Field Work | % 0 | |
Special Course Internship (Work Placement) | % 0 | |
Quizzes | % 0 | |
Homework Assignments | % 0 | |
Presentation | % 0 | |
Project | 1 | % 35 |
Seminar | % 0 | |
Midterms | 1 | % 25 |
Preliminary Jury | % 0 | |
Final | 1 | % 40 |
Paper Submission | % 0 | |
Jury | % 0 | |
Bütünleme | % 0 | |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 25 | |
PERCENTAGE OF FINAL WORK | % 75 | |
Total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 3 | 42 |
Laboratory | 0 | 0 | 0 |
Application | 0 | 0 | 0 |
Special Course Internship (Work Placement) | 0 | 0 | 0 |
Field Work | 0 | 0 | 0 |
Study Hours Out of Class | 14 | 4 | 56 |
Presentations / Seminar | 1 | 15 | 15 |
Project | 1 | 90 | 90 |
Homework Assignments | 0 | 0 | 0 |
Quizzes | 0 | 0 | 0 |
Preliminary Jury | 0 | 0 | 0 |
Midterms | 1 | 40 | 40 |
Paper Submission | 0 | 0 | 0 |
Jury | 0 | 0 | 0 |
Final | 1 | 60 | 60 |
Total Workload | 303 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Ability to identify and apply advanced concepts in computer engineering | |
2) | Cooperate efficiently in intra-disciplinary and multi-disciplinary teams. | |
3) | Have theoretical and practical basis in computer engineering and science to be able to conduct related academic research independently. | |
4) | Ability to apply advanced mathematical and engineering knowledge on real problems. | |
5) | Ability to search the scientific literature related to a research project and find the relationships with own research | |
6) | Ability to interprete scientific research and use the findings | |
7) | Ability to work efficiently in interdisciplinary research teams | |
8) | Ability to attain scientific knowledge | |
9) | Ability find ways to improve upon current knowledge | |
10) | Ability to present research findings in seminars and conferences | |
11) | Ability to write research progress reports by referring to published theses and papers. | |
12) | Ability to show the responsibility of professional and ethical behavior |