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Information
| Unit | FACULTY OF ENGINEERING |
| INDUSTRIAL ENGINEERING PR. | |
| Code | ENM248 |
| Name | Statistical Research Methods |
| Term | 2018-2019 Academic Year |
| Semester | 4. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 4 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Label | E Elective |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. EBRU YILMAZ |
| Course Instructor |
Doç. Dr. EBRU YILMAZ
(Bahar)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
The aim of this course is to give basic statistical research methods used in some researches and studies.
Course Content
Statistical applications in engineering, Data collection and analysis methods, Probability distributions, Confidence intervals, Hypothesis tests, Experimental design, Analysis of variance, Regression modeling.
Course Precondition
Yok
Resources
Notes
1. MONTGOMERY, D.C., RUNGER, G.C., and HUBELE, N.F., 2011, Engineering Statistics (Fifth Edition), John Wiley & Sons, Inc.2. AKDENİZ, F., 1996, Olasılık ve İstatistik, Genişletilmiş Baskı, Baki Kitabevi, Adana, 700 sayfa
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Explains various concepts such as mean, median, mode, variance, standard deviation. |
| LO02 | Calculates confidence intervals for statistical problems. |
| LO03 | Sets up hypothesis tests on statistical problems. |
| LO04 | Explains the importance of experimental design for statistical applications. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Has sufficient background on topics related to mathematics, physical sciences and industrial engineering. | 5 |
| PLO02 | - | Gains ability to use the acquired theoretical knowledge on basic sciences and industrial engineering for describing, formulating and solving an industrial engineering problem, and to choose appropriate analytical and modeling methods. | 5 |
| PLO03 | - | Gains ability to analyze a service and/or manufacturing system or a process and describes, formulates and solves its problems . | 4 |
| PLO04 | - | Gains ability to choose and apply methods and tools for industrial engineering applications. | 4 |
| PLO05 | - | Can collect and analyze data required for industrial engineering problems ,develops and evaluates alternative solutions. | 5 |
| PLO06 | - | Works efficiently and takes responsibility both individually and as a member of a multi-disciplinary team. | 4 |
| PLO07 | - | Can access information and to search/use databases and other sources for information gathering. | 4 |
| PLO08 | - | Appreciates life time learning; follows scientific and technological developments and renews himself/herself continuously. | 4 |
| PLO09 | - | Can use computer software in industrial engineering along with information and communication technologies. | 4 |
| PLO10 | - | Can use oral and written communication efficiently. | 4 |
| PLO11 | - | Uses English skills to follow developments in industrial engineering and to communicate with people in his/her profession. | 4 |
| PLO12 | - | Has a conscious understanding of professional and ethical responsibilities. | 5 |
| PLO13 | - | Has a necessary consciousness on issues related to job safety and health, legal aspects of environment and engineering practice. | 3 |
| PLO14 | - | Becomes competent on matters related to project management, entrepreneurship, innovation and has knowledge about current matters in industrial engineering. | 3 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Statistical applications in engineering | Reading the resources related to the section | |
| 2 | Data collection and analysis methods | Reading the resources related to the section | |
| 3 | Data collection and analysis methods | Reading the resources related to the section | |
| 4 | Probability distributions | Reading the resources related to the section | |
| 5 | Probability distributions | Reading the resources related to the section | |
| 6 | Confidence intervals | Reading the resources related to the section | |
| 7 | Confidence intervals | Reading the resources related to the section | |
| 8 | Mid-Term Exam | The preparation for the mid-term exam | |
| 9 | Hypothesis tests | Reading the resources related to the section | |
| 10 | Hypothesis tests | Reading the resources related to the section | |
| 11 | Experimental design | Reading the resources related to the section | |
| 12 | Experimental design | Reading the resources related to the section | |
| 13 | Analysis of variance | Reading the resources related to the section | |
| 14 | Analysis of variance | Reading the resources related to the section | |
| 15 | Regression modeling | Reading the resources related to the section | |
| 16 | Term Exams | The preparation for the final exam | |
| 17 | Term Exams | The preparation for the final exam |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 100 | 40 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 7 | 7 |
| Final Exam | 1 | 18 | 18 |
| Total Workload (Hour) | 109 | ||
| Total Workload / 25 (h) | 4,36 | ||
| ECTS | 4 ECTS | ||