University of Mary Hardin-Baylor

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1 University of Mary Hardin-Baylor Contact Information Instructor: Dr. William G. Tanner, Jr. Office: Davidson 119 Office Phone: 254.295.4645 E-mail: btanner@umhb.

Mathematics Majors, ENGR 3391 (Sections 01 & 02).

1 1 University of Mary Hardin-Baylor Contact Information Instructor: Dr. William G. Tanner, Jr. Office: Davidson 119 Office Phone: Office Hours: MW 3:30 pm 5:00 pm TTh 1:00 pm 3:00 pm Other times by appointment Description of the Course Course Name, Number and Section: Special Topics: Numerical Analysis for CSE and Mathematics Majors, ENGR 3391 (Sections 01 & 02). Term: Spring 2015 Catalog Description: This course is designed to familiarize computer science and engineering students with the fundamental concepts in numerical algorithms. This course will consider problems from the following areas? root finding, floating pair systems, finding solutions to linear systems using direct or iterative solvers, interpolation curve fitting, numerical differentiation and integration, multiple integrals, least squares. Prerequisite (s): CISC 2330 or ENGR 1320, and CISC 2315 or MATH 1330 or by permission of the instructor. Lab Fee. Time/Location Course Meets: MWF 12:00-12:50 PM in Davidson 101 Course Objectives: It is the intent of this course to elucidate the connection between specific concepts of theoretical mathematics and number crunching in order that the student may obtain practical results from an engineering analysis. Intentional use will be made of the numerical language MATLAB to implement and analyze numerical algorithms. To provide the student with the necessary mathematical skills to solve equations numerically, the following subjects will be addressed in this course during the MATLAB sessions: Taylor polynomials, representations of numbers, error analysis, root finding, interpolation, numerical integration and differentiation, and linear systems. Relationship of Course to Engineering Science Program Learning Outcomes:

2 2 A successful student will strongly contribute to the CSE Learning Outcomes and will demonstrate: 1. an ability to apply knowledge of mathematics, science, and engineering 2. an ability to design and conduct experiments, as well as to analyze and interpret data 3. an ability to design a system, component, or process to meet desired needs 4. an ability to function on multi-disciplinary teams 5. an ability to identify, formulate, and solve engineering problems 6. a recognition of the need for, and an ability to engage in life-long learning 7. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice Credit Hour(s): This is a traditional, 3-credit hour course. Each credit hour earned in this course requires at least fifteen (15) contact hours, as well as a minimum of thirty (30) hours of student homework. Textbook: Chapra, Steven. Applied Numerical Methods W/MATLAB: for Engineers & Scientists, 3rd Edition. McGraw-Hill, Academic Honesty: The University of Mary Hardin-Baylor policy on academic integrity applies to all courses. UMHB expects the highest standards of academic integrity among all members of the campus community. All acts of plagiarism or violations of academic honesty are considered serious offenses and may result in failure of the assignment or the course. Special Accommodations: If you have a disability for which you are or may be requesting an accommodation, you are encouraged to contact both your professor and the Accommodation & Student Assistance Program office in the Robert & Linda Black Center for Counseling, Testing & Health Services, Mabee Student Center, Suite 310, as early as possible in the term. Course Structure: The focus of the class meeting time for this course is on group discussion of the material and the solving of difficult problems by students working in small groups. Students are expected to come to class prepared for the material being discussed that day. Lectures over basic material will be posted on the course webpage prior to the scheduled class time. Every student will be expected to have already done the assigned reading, watched the posted lecture, and completed elementary problems relating to the topic that is the subject of the class. Your learning will be evaluated with online quizzes prior to each class period. The quizzes are designed to both test your knowledge of the material and help you gage the level of mastery that will be expected. As such, the quizzes can be retaken an unlimited number of

3 3 times until you are content with the outcome. In between trials of the quizzes, you should look back at the material to learn portions that were missed on the quiz. Assignments and Grading: Assignments should include everything listed below. Course Requirements follow, along with how each assignment is used and weighted to determine a grade. Problem Sets and Quizzes (weighted equally) 10% Project Reports 30% Four Section Examinations (worth 10% each) 40% Final Examination 20% Course Requirements: 1. Work assignments in the text as they are given. Quizzes over the chapter readings and homework will be given periodically. 2. Show progress in the course through four examinations. 3. Participate in in-class activities. Much of the material will be presented in the reading and then reinforced in class. Your participation in the activities during class will greatly affect your performance in this course. 4. Contribute to 4 team-based class projects. These projects will require writing code and documenting results. Your participation in these projects will be evaluated by your peers and insufficient contributions will be penalized. 5. Take and pass the cumulative final examination. A failing grade on the final exam will be grounds for failing the course. Grade Scale: A = 91 to 100 B = 81 to 90 C = 71 to 80 D = 61 to 70 F = < 60 Please note grade point cut-off points. Always monitor your current performance level via MyCampus. Late Work Policy: Makeup examinations and quizzes will be given only under extenuating circumstances (major illness, death in the family, etc.). Students desiring a Makeup examination or quiz must make arrangements with the professor. A Makeup examination must be scheduled before the next scheduled examination. If a student fails to take a Makeup examination before the next scheduled examination, that student will receive a zero for the examination missed. Some assignments may be eligible to be turned in late at a discounted grade. Late assignments will be discounted at the rate of one letter grade per day. After four days, the assignment will not be accepted. All assignments are due at the beginning of the

4 4 class session. If they are turned in after the beginning of the class session, the score will be discounted by one letter grade. Assignments related to class presentations, projects, guided discussions, or similar activities, may not be eligible for late submission. Assignments missed due to university approved absences or specific individually documented instances (note from a doctor in the case of illness or absences due to legal or civil proceedings) are eligible for late submission. Professors/instructors should be notified prior to a university approved absence. Early Work Policy: Assignments (including team projects but excluding quizzes) that are turned in more than 24 hours before the deadline will be given a 5% extra credit bonus. All assignments should be turned in directly to the professor, and extra credit should be acknowledged at the time of submission. Academic Decorum: The learning process involves an exchange of ideas and an exploration of concepts between faculty and students and a certain level of decorum facilitates this process. Supportive actions include: (1) Coming to class prepared including reading all assignments. (2) Being attentive and responsive in class. (3) Respecting the course instructor and fellow students (opinions and ideas). (4) Contributing to the class by making topic-specific comments. (5) Offering critiques and alternative ideas in a non-condescending manner. (6) Providing a fair share of work to group projects and team activities. Examples of disruptive behaviors to avoid include: (1) Talking, sleeping, or otherwise distracting members of the class. (2) Using electronic devices for personal use. (3) Exhibiting argumentative or attention-seeking behavior. (4) Failing to show respect or act with civility. Attendance Policy: Class attendance is viewed by the instructor as critically important and imperative to success in this course are expected to be present at all class meetings. If you are absent, you have a responsibility to submit work that is due for that class period by a) sending it with another person in class, or b) turning it in personally to the professor prior to the due date. The assignment must be posted as received no later than the beginning of the class time on the date it is due. Additionally, you have a responsibility to inquire of other students in class for notes, materials, and assignments from classes you miss.

5 5 Schedule of Course Activities: The schedule of course activities are included in a calendar below. The topics and dates are tentative and subject to possible revision/change, should the need arise. Day Topic Reading Major Assignments Due 12-Jan Syllabus and Introduction NONE 14-Jan Matlab Fundamentals 1 16-Jan Matlab Fundamentals 2 19-Jan MARTIN LUTHER KING DAY - NO CLASS 21-Jan Structured Programming Fundamentals Jan Nesting and Function Passing Jan Numerical Error 4 28-Jan Root Finding - Bisection Method 5 30-Jan Project 1 2-Feb Newton Rhapson Method Feb Secant Method Feb EXAM 1 9-Feb One Dimensional Optimization Project 1 Due 11-Feb PRESIDENT GEORGE W BUSH SPEECH - NO CLASS 13-Feb Multi-Dimensional Optimization Feb Project 2 18-Feb Matrix Algebra 8 20-Feb Gaussian Elimination Feb Gaussian Elimination Feb LU Factorization 10 Project 2 Due 27-Feb Loops, Matrix Inverse 11 2-Mar EXAM 2 4-Mar Solving Linear Systems 12 6-Mar Eigenvalues 13 9-Mar Curve Fitting Mar Linearization Mar Polynomial Regression Mar 18-Mar 20-Mar 23-Mar SPRING BREAK Project 3 25-Mar Polynomial Interpolation Mar Splines and Piecewise Interpolation Mar Simple Numerical Integration Apr Trapezoidal Rule 19.3 Project 3 Due 3-Apr EXAM 3

6 6 6-Apr Simpson's Rule Apr Quadrature Apr Ordinary Differential Equations Overview (p.547) 13-Apr Euler's Method Apr Runge-Kutta Methods Apr EXAM 4 20-Apr Project 4 22-Apr Boundary Value Problems Apr Shooting Method Apr Review 29-Apr Review Project 4 Due May FINAL EXAM (1:00 pm)

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