ECTS - Probability and Statistics

Probability and Statistics (IE220) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Probability and Statistics IE220 4. Semester 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Service Courses Taken From Other Departments
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Question and Answer, Problem Solving.
Course Coordinator
Course Lecturer(s)
  • Instructor Dr. Burcu DEVRİM İÇTENBAŞ
Course Assistants
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;
  • Students will acquire and apply fundamental concepts of probability theory to engineering problems.
  • Students will develop an insight about the role of statistics for different engineering disciplines.
  • Students will be able to evaluate and solve real life processes and problems using statistical applications.
  • Students will be able to use a suitable computer-based statistical package for statistical analysis.
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
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.
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
Percentage of Final Work 40
Total 100

Course Category

Core Courses
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
1 2 3 4 5
1 Has adequate knowledge in mathematics, science, and computer engineering-specific subjects; uses theoretical and practical knowledge in these areas to solve complex engineering problems. X
2 Identifies, defines, formulates, and solves complex engineering problems; selects and applies appropriate analysis and modeling methods for this purpose. X
3 Designs a complex system, process, device, or product to meet specific requirements under realistic constraints and conditions; applies modern design methods for this purpose.
4 Develops, selects, and uses modern techniques and tools necessary for the analysis and solution of complex problems encountered in computer engineering applications; uses information technologies effectively. X
5 Designs experiments, conducts experiments, collects data, analyzes and interprets results for the investigation of complex engineering problems or research topics specific to the discipline of computer engineering. X
6 Works effectively in disciplinary and multidisciplinary teams; gains the ability to work individually.
7 Communicates effectively in Turkish, both orally and in writing; writes effective reports and understands written reports, prepares design and production reports, makes effective presentations, gives and receives clear and understandable instructions.
8 Knows at least one foreign language; writes effective reports and understands written reports, prepares design and production reports, makes effective presentations, gives and receives clear and understandable instructions.
9 Has awareness of the necessity of lifelong learning; accesses information, follows developments in science and technology, and continuously improves oneself.
10 Acts in accordance with ethical principles and has awareness of professional and ethical responsibility.
11 Has knowledge about the standards used in computer engineering applications.
12 Has knowledge about workplace practices such as project management, risk management, and change management.
13 Gains awareness about entrepreneurship and innovation.
14 Has knowledge about sustainable development.
15 Has knowledge about the health, environmental, and safety impacts of computer engineering applications in universal and societal dimensions and the contemporary issues reflected in the field of engineering.
16 Gains awareness of the legal consequences of engineering solutions.
17 Analyzes, designs, and expresses numerical computation and digital representation systems. X
18 Uses programming languages and appropriate computer engineering concepts to solve computational problems. X

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
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