ECTS - Probability and Statistics
Probability and Statistics (IE220) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Probability and Statistics | IE220 | 4. Semester | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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N/A |
Course Language | English |
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Course Type | Compulsory Departmental Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture, Question and Answer, Problem Solving. |
Course Lecturer(s) |
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Course Objectives | In this course, the students will be learning fundamental concepts of the probability and statistics so that they can solve practical problems of engineering which requires statistical techniques. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Introduction to probability and statistics; random variables and probability distributions; expected value; sampling distributions; one and two sample estimation problems; test of hypotheses; simple linear regression. |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | The role of probability and statistics in engineering | [1] pages 1-15 |
2 | Descriptive Statistics-Numerical Summary | [1] pages 191-214 |
3 | Descriptive Statistics-Graphical Summary | [1] pages 191-214 |
4 | Probability | [1] pages 17-57 |
5 | Probability | [1] pages 17-57 |
6 | Random Variables | [1] pages 67-74 [1] pages 108-114 |
7 | Midterm 1 | |
8 | Discrete Probability Distributions | [1] pages 79-97 |
9 | Continuous Probability Distributions | [1] pages 116-127 |
10 | Sampling Distributions | [1] pages 223-231 |
11 | Point and Interval Estimation | [1] pages 253-263 |
12 | Point and Interval Estimation | [1] pages 253-263 |
13 | Hypothesis Testing | [1] pages 283-314 |
14 | Midterm 2 | |
15 | Inference for two samples | [1] pages 351-368 |
16 | Simple Linear Regression | [1] pages 401-440 |
Sources
Course Book | 1. Montgomery, D.C., and Runger, G.C., Applied Statistics and Probability for Engineers, John Wiley and Sons, Inc., 4th Edition, June 2006. |
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Other Sources | 2. Walpole, R.E. , Myers, R.H., Myers, S.L. an Ye, K., Probability and Statistics for Engineers and Scientists, Prentice Hall, 8th edition, 2007. |
3. Milton, J.S. and Arnold, J.C., Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences, McGraw-Hill, 4th edition, 2002. | |
4. Ross, S., Introduction to Probability and Statistics for Engineers and Scientists, Academic Press, 3rd edition, 2004. | |
5. Triola, M.F., Essentials of Statistics, Addison Wesley,2nd edition, 2004. |
Evaluation System
Requirements | Number | Percentage of Grade |
---|---|---|
Attendance/Participation | - | - |
Laboratory | - | - |
Application | - | - |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | 4 | 20 |
Presentation | - | - |
Project | - | - |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 2 | 40 |
Final Exam/Final Jury | 1 | 40 |
Toplam | 7 | 100 |
Percentage of Semester Work | 60 |
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Percentage of Final Work | 40 |
Total | 100 |
Course Category
Core Courses | |
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Major Area Courses | |
Supportive Courses | X |
Media and Managment Skills Courses | |
Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
# | Program Qualifications / Competencies | Level of Contribution | ||||
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1 | 2 | 3 | 4 | 5 | ||
1 | Adequate knowledge in mathematics, science and computing fields; ability to apply theoretical and practical knowledge of these fields in solving engineering problems related to information systems. | X | ||||
2 | Ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. | X | ||||
3 | Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose. | |||||
4 | Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in information systems engineering applications; ability to use information technologies effectively. | X | ||||
5 | Ability to gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the information systems discipline. | X | ||||
6 | Ability to work effectively in inter/inner disciplinary teams; ability to work individually. | |||||
7 | a. Effective oral and written communication skills in Turkish; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. b. Knowledge of at least one foreign language; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. | |||||
8 | Recognition of the need for lifelong learning; the ability to access information and follow recent developments in science and technology with continuous self-development. | |||||
9 | a. Ability to behave according to ethical principles, awareness of professional and ethical responsibility. b. Knowledge of the standards utilized in information systems engineering applications. | |||||
10 | a. Knowledge on business practices such as project management, risk management and change management. b. Awareness about entrepreneurship, and innovation. c. Knowledge on sustainable development. | |||||
11 | a. Knowledge of the effects of information systems engineering applications on the universal and social dimensions of health, environment, and safety. b. Awareness of the legal consequences of engineering solutions. |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
Laboratory | |||
Application | |||
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | 16 | 3 | 48 |
Presentation/Seminar Prepration | |||
Project | |||
Report | |||
Homework Assignments | 4 | 5 | 20 |
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 2 | 3 | 6 |
Prepration of Final Exams/Final Jury | 1 | 3 | 3 |
Total Workload | 125 |