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Course Description Course Name : Numerical Analysis Course Code : ENM232 Course Type : Compulsory Level of Course : First Cycle Year of Study : 2 Course Semester : Spring (16 Weeks) ECTS : 4 Name of Lecturer(s) : Asst.Prof.Dr. ZEYNEP YAPTI ÖZKURT Learning Outcomes of the Course : Interprets sources of error in numerical solutions. Calculates the roots of a function. Solves linear equation sytems. Finds inverse of a matrix. Calculates aproximate values of polynomial functions with one variable. Calculates numerical integration. Analyzes errors in numerical calculations. Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : This course aims to introduce a variety of methods of numerical analysis and to solve the mathematical problems in different areas with the methods of numerical analysis. Course Contents : Solution methods for non-linear equations, Solution methods for systems of linear equations. Interpolatiom. Numerical Integration Methods. Language of Instruction : Turkish Work Place : IE classrooms   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Importance and meaning of numerical analysis , Number systems and errors in numerical procedures review of the related chapter from the textbook lecture, problem solving 2 Bisection and Newtons method review of the related chapter from the textbook lecture, problem solving 3 Bairstow method review of the related chapter from the textbook lecture, problem solving 4 Linear equation systems, Inverse of a matrix, Deternimant review of the related chapter from the textbook lecture, problem solving 5 Gauss and Gauss-Jordan Methods review of the related chapter from the textbook lecture, problem solving 6 Gauss and Gauss-Jordan Methods for finding Inverse of a matrix and Deternimant review of the related chapter from the textbook lecture, problem solving 7 Gauss-Seidel method for solving Linear equations review of the related chapter from the textbook lecture, problem solving 8 Midterm exam prepare for the exam written exam 9 Interpolation, Linear interpolation, Lagrange interpolation review of the related chapter from the textbook lecture, problem solving 10 Divided differences interpolation review of the related chapter from the textbook lecture, problem solving 11 Differences İnterpolation review of the related chapter from the textbook lecture, problem solving 12 Differences İnterpolation review of the related chapter from the textbook lecture, problem solving 13 Calcutation Methods for Numerical integration review of the related chapter from the textbook lecture, problem solving 14 Calcutation Methods for Numerical integration on an interval review of the related chapter from the textbook lecture, problem solving 15 Exercises review of the related chapter from the textbook lecture, problem solving 16/17 Final examination prepare for the exam written exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Behic Cagal (1989), Numerical Analysis, Seç Yayın Dağıtım, İstanbul.  Lee W. Johnson, R. Dean Riess (1982) Numerical Analysis, Addison-Wesley Publishing Company. Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 50     Homeworks/Projects/Others 5 50 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Can collect and analyze data required for industrial engineering problems ,develops and evaluates alternative solutions. 3 2 Has sufficient background on topics related to mathematics, physical sciences and industrial engineering. 2 3 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. 2 4 Gains ability to analyze a service and/or manufacturing system or a process and describes, formulates and solves its problems . 1 5 Gains ability to choose and apply methods and tools for industrial engineering applications. 1 6 Can access information and to search/use databases and other sources for information gathering. 1 7 Works efficiently and takes responsibility both individually and as a member of a multi-disciplinary team. 1 8 Appreciates life time learning; follows scientific and technological developments and renews himself/herself continuously. 1 9 Can use computer software in industrial engineering along with information and communication technologies. 0 10 Can use oral and written communication efficiently. 2 11 Has a conscious understanding of professional and ethical responsibilities. 0 12 Uses English skills to follow developments in industrial engineering and to communicate with people in his/her profession. 0 13 Has a necessary consciousness on issues related to job safety and health, legal aspects of environment and engineering practice. 0 14 Becomes competent on matters related to project management, entrepreneurship, innovation and has knowledge about current matters in industrial engineering. 0 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 3 3 9     Out of Class Study (Preliminary Work, Practice) 10 5 50 Assesment Related Works     Homeworks, Projects, Others 5 5 25     Mid-term Exams (Written, Oral, etc.) 1 2 2     Final Exam 1 2 2 Total Workload: 88 Total Workload / 25 (h): 3.52 ECTS Credit: 4