IE568 STATISTICAL APPLICATIONS IN ENGINEERING
| Course Code: | 5680568 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Industrial Engineering |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | Assoc.Prof.Dr. SEÇİL SAVAŞANERİL TÜFEKCİ |
| Offered Semester: | Fall or Spring Semesters. |
Course Objectives
At the end of the course, the students will,
1. understand and use descriptive statistics with the support of statistical packages.
2. be able understand and use inferential statistics with the support of statistical packages.
3. be able to construct and analyze models of empirical relationships between variables.
Course Content
Computer aided exploration, analysis and classification of data and empirical model building in engineering through the use of descriptive statistics, random sampling, probability distribution fitting, analysis of variance, regression analysis, discrimination and classification and clustering
Course Learning Outcomes
The following are the learning outcomes. At the end of the course the students will be able to:
1. construct graphical representations of data, interpret the graphs using statistical packages.
2. compute the numerical values of the sample statistics and interpret them.
3. find confidence intervals of the unknown parameters of the distributions from observed samples.
4. test the statistical hypothesis about the unknown parameters of the distributions from an observed sample, compute related error probabilities with the support of statistical packages.
5. construct/estimate a linear model (using regression and design of experiments) with single and multiple independent variables.
6. perform the significance tests, residual analysis and model transformation.
Program Outcomes Matrix
| Contribution | |||||
| # | Program Outcomes | No | Yes | ||
| 1 | Specialize with advanced knowledge in selected areas of Industrial Engineering; such as Production and Operations Management, Supply Chain Management, Business Analytics and Information Systems, Decision Sciences and Operational Research, Quality Management, Human Factors and Ergonomics, and Strategy and Industrial Economics. | ✔ | |||
| 2 | Have advanced ability to formulate and solve industrial engineering problems. | ✔ | |||
| 3 | Be able to systematically acquire new scientific knowledge to design and improve socio-technical systems. | ✔ | |||
| 4 | Be able to conduct scientific research in industrial engineering. | ✔ | |||
| 5 | Be able to apply critical reasoning in their professional careers. | ✔ | |||
| 6 | Appreciate the academics ethics. | ✔ | |||