umi.fbe.ieu.edu.tr
Course Name | |
Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
---|---|---|---|---|---|
Fall/Spring |
Prerequisites | None | |||||
Course Language | ||||||
Course Type | Elective | |||||
Course Level | - | |||||
Mode of Delivery | - | |||||
Teaching Methods and Techniques of the Course | ||||||
Course Coordinator | - | |||||
Course Lecturer(s) | ||||||
Assistant(s) | - |
Course Objectives | |
Learning Outcomes | The students who succeeded in this course;
|
Course Description |
| Core Courses | X |
Major Area Courses | ||
Supportive Courses | ||
Media and Managment Skills Courses | ||
Transferable Skill Courses |
Week | Subjects | Required Materials |
1 | Why to study statistics and the concept of decision making in an uncertain environment. Importance of describing data and summarizing descriptive relationships. | You need to follow the lecture notes. |
2 | Obtaining meaningful data, presenting data. Data presentation errors. | You need to follow the lecture notes. |
3 | Descriptive Measures: Measures of central tendency, Measures of variability. | You need to follow the lecture notes. |
4 | Measures of Relative location. | You need to follow the lecture notes. |
5 | Methods for detecting Outliers. Obtaining bivariate linear relationships. | You need to follow the lecture notes. |
6 | General principles for analyzing data: Concept of sampling, Unbiasedness and minimum variance, the sampling distribution of the sample mean and the Central limit theorem. | You need to follow the lecture notes. |
7 | General principles for analyzing data: Single sample estimation with confidence intervals and Tests of Hypothesis. | You need to follow the lecture notes. |
8 | General principles for analyzing data: Two samples estimation with confidence intervals and Tests of Hypothesis. | You need to follow the lecture notes. |
9 | Design of Experiments | You need to follow the lecture notes. |
10 | Analysis of Variance. | You need to follow the lecture notes. |
11 | Simple Linear Regression. | You need to follow the lecture notes. |
12 | Multiple Regression and model building. | You need to follow the lecture notes. |
13 | Categorical Data analysis. | You need to follow the lecture notes. |
14 | Nonparametric Statistical analysis. | You need to follow the lecture notes. |
15 | Some selected topics and applications | You need to follow the lecture notes. |
16 | Review of the Semester |
Course Notes/Textbooks | The extracts above and exercises will be given. |
Suggested Readings/Materials | Statistical Techniques for Data Analysis” by J.K. Taylor and C. Cihon, Chapman&Hall.“Statistical Inference” by G. Casella and R. L. Berger, Duxbury Press |
Semester Activities | Number | Weigthing |
Participation | ||
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques | ||
Portfolio | ||
Homework / Assignments | ||
Presentation / Jury | ||
Project | 1 | 20 |
Seminar / Workshop | ||
Oral Exam | ||
Midterm | 1 | 30 |
Final Exam | 1 | 50 |
Total |
Weighting of Semester Activities on the Final Grade | 50 | |
Weighting of End-of-Semester Activities on the Final Grade | 50 | |
Total |
Semester Activities | Number | Duration (Hours) | Workload |
---|---|---|---|
Course Hours (Including exam week: 16 x total hours) | 16 | 3 | 48 |
Laboratory / Application Hours (Including exam week: 16 x total hours) | 16 | ||
Study Hours Out of Class | 15 | 6 | |
Field Work | |||
Quizzes / Studio Critiques | |||
Portfolio | |||
Homework / Assignments | |||
Presentation / Jury | |||
Project | 1 | 10 | |
Seminar / Workshop | |||
Oral Exam | |||
Midterms | 1 | 32 | |
Final Exams | 1 | 45 | |
Total | 225 |
# | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
1 | To develop and deepen his/her knowledge on theories of mathematics and statistics and their applications in level of expertise, and to obtain unique definitions which bring innovations to the area, based on master level competencies, | X | ||||
2 | To have the ability of original, independent and critical thinking in Mathematics and Statistics and to be able to develop theoretical concepts, | X | ||||
3 | To have the ability of defining and verifying problems in Mathematics and Statistics, | X | ||||
4 | With an interdisciplinary approach, to be able to apply theoretical and applied methods of mathematics and statistics in analyzing and solving new problems and to be able to discover his/her own potentials with respect to the application, | X | ||||
5 | In nearly every fields that mathematics and statistics are used, to be able to execute, conclude and report a research, which requires expertise, independently, | X | ||||
6 | To be able to evaluate and renew his/her abilities and knowledge acquired in the field of Applied Mathematics and Statistics with critical approach, and to be able to analyze, synthesize and evaluate complex thoughts in a critical way, | X | ||||
7 | To be able to convey his/her analyses and methods in the field of Applied Mathematics and Statistics to the experts in a scientific way, | X | ||||
8 | To be able to use national and international academic resources (English) efficiently, to update his/her knowledge, to communicate with his/her native and foreign colleagues easily, to follow the literature periodically, to contribute scientific meetings held in his/her own field and other fields systematically as written, oral and visual. | X | ||||
9 | To be familiar with computer software commonly used in the fields of Applied Mathematics and Statistics and to be able to use at least two of them efficiently, | X | ||||
10 | To contribute the transformation process of his/her own society into an information society and the sustainability of this process by introducing scientific, technological, social and cultural advances in the fields of Applied Mathematics and Statistics, | X | ||||
11 | As having rich cultural background and social sensitivity with a global perspective, to be able to evaluate all processes efficiently, to be able to contribute the solutions of social, scientific, cultural and ethical problems and to support the development of these values, | X | ||||
12 | As being competent in abstract thinking, to be able to connect abstract events to concrete events and to transfer solutions, to analyze results with scientific methods by designing experiment and collecting data and to interpret them, | X | ||||
13 | To be able to produce strategies, policies and plans about systems and topics in which mathematics and statistics are used and to be able to interpret and develop results, | X | ||||
14 | To be able to evaluate, argue and analyze prominent persons, events and phenomena, which play an important role in the development and combination of the fields of Mathematics and Statistics, within the perspective of the development of other fields of science, | X | ||||
15 | In Applied Mathematics and Statistics, to be able to sustain scientific work as an individual or a group, to be effective in all phases of an independent work, to participate decision-making process and to make and execute necessary planning within an effective time schedule. | X |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest