This page was last modified on August 22, 2017 05:49:23pm EDT Syllabus ISE500

Instructor:

Geza Bottlik , E-mail: bottlik@usc.edu

Office Hours:

Tuesday/Thursday, 2:00 P.M. – 3:00 P.M. Room GER 202 or by appointment

 

Phone 213 740 - 5050 (Class days only)

TA:

Xiang Gao xiangg@usc

TA Office Hours:

Thursday 3:30 P.M. – 5:30 P.M. RTH319

Class time/place:

Tuesdays/Thursdays 11:00 A.M. – 12:20 P.M., OHE100B

Dowloadable PDF

 

 

Test Schedule:

Midterm 1:

Tuesday, September 19, 2017

11:00 A.M. – 12:20 P.M

Midterm 2:

Thursday, November 2, 2017

11:00 A.M. – 12:20 P.M

Final:

Tuesday, December 12, 2017

8:00 A.M. – 10:00 A.M.

 

Web Page:                            www.gezabottlik.com
      At the site you will find:

  • The syllabus, grades, resumes, Lecture Notes
  • Assignments and due dates, solutions

                  Your responsibility:

  • Register on the site and learn how to use it
  • Download the lecture notes and assignments for each class
  • Review and verify your grades to track your progress and standing in the class.

The DEN  website (courses.uscden.net) is only used for e-mail, the discussion board and assignment upload and return. Check your email on a regular basis

Required Text:
Jay L. Devore “Probability and Statistics for Engineering and the Sciences “, 8th Edition, Brooks/Cole, 2009, ISBN-13:978-0-538-73352-6

References:
Sheldon M. Ross “Probability and Statistics for Engineers and Scientists”, 4th Editions, Academic Press, 2009, ISBN 13:978-0-12-370483-2
Roger B. Myerson “Probability Models for Economic Decisions” , Thomson Brooks/Cole,  2005 ISBN 0-534-42381-7
Raiffa, Richardson and Metcalfe “Negotiation Analysis”, by, Harvard University Press, 2002 ISBN 0 – 674 – 008890 –1
Robert L. Winkler “An Introduction to Bayesian Inference and Decision”, 2nd Edition, Probabilistic Publishing, 2003

Assignments: Readings and Problems will be included in most weeks' assignments. It is imperative that you prepare for class  -- you will find it extremely difficult to follow the discussion if you have not read the material. Usually, problems are assigned on Tuesday and are due on the following Monday at midnight. We will return the assignments one week later on the assignment manager if points have been deducted. Late homework cannot be accepted, unless prior arrangements have been made (e.g. out of town funeral). Homework is to be in digital format, a single printable document (no zip files), submitted through the assignment manager on D2L.
Your name, assignment number, the date and with whom you worked must be in the header. Use a consistent template and format the output for a professional appearance. The assignments should be as professional in appearance as if you were preparing reports at work or for publication. Clearly label your conclusions for each problem, followed by the supporting calculations and discussion. The problems must be in the order assigned. Out of sequence problems will receive no credit.
It’s OK to work on homework together, but finish it by yourself and indicate with whom you worked in the header. Each student must turn in a separate homework, unless the assignment is specified as a team assignment. Generated data and essay questions must be unique to each student. Do not give your files to others and do not use others’ files. Do not copy problems. Homework files will be named by the assignment manager, so keep your names very short – otherwise we have to truncate them in order to open them. The same rules apply among teams for team assignments. If you used a solution from a prior semester, indicate so. If the answer is given in a book, don’t just copy it, explain how you got it.

Objectives of the course
The major objective of this course is to have you understand, interpret and verify the results obtained from statistical analyses. Secondly, given a situation or problem, you will learn which statistical tools are the appropriate ones to assess the problem or situation.
This course is intended to train future engineering managers in the most commonly used statistical methods in decision making with partial information in an uncertain environment. Such decisions include (i) data analyses that are appropriate for generating information useful in decision making and (ii) a framework for analyzing decisions based on partial information.

The class is designed to be practical in its approach and of value to both line and staff managers. Students who are employed are STRONGLY encouraged to bring procedures, problems or issues which the students deal with on a daily basis to the attention of the instructor.

 The specific course objectives include enabling the student to:
                         Be familiar with the basics of decision making
                         Understand the importance of statistical analysis in managerial decisions.
                         Understand the importance and limitations of data gathering
                         Use statistical tools in decision making.
                         Interpret the outcome and meaning of statistical information.
                         Understand the limitations of the use of statistical methods
                         Have knowledge of the use of statistical tools in contemporary management

 

Grading:

                                         

Homework, 1.5 points each

~18%

Midterm 1

~12%

Midterm 2

~20%

Final exam

~27%

Participation (attendance, quizzes, asking questions, making contributions, postings on the discussion board) 1.5 pts. each for quizzes, 0.3 for others

~23%

The grade for the course will only be based on the required work listed above and cannot be improved with additional work. Note that 25% of the grade is for participation – so participate!

Grades are based upon your personal comprehension of the material and your performance on the exams and assignments relative to the other students. The quality of your fellow classmates as students is expected to be quite high and the expectations of the instructor are established accordingly.

Quizzes:

     There will be a quiz every week at the start of class on Tuesday or Thursday.  The format is mostly True/False. The purpose of these quizzes is to encourage you to keep up with the class material. I anticipate that you will have little difficulty in answering the questions if you are up to date on the class materials, including those for the next class. There is normally no make-up of a missed quiz. However, if a student expects to be away from class for a valid reason (e.g. employment travel) then special arrangements can be made to allow the quiz to be taken on-line.  The quiz each week will be based primarily upon two subjects: the material from the previous week and the reading assignment for that week. You are expected to have read the weekly assignment prior to the start of class. The quizzes are open notes, book and laptop.

Examinations:

The midterms and final exams are open book and open notes.  Calculators and laptops may be used. Exam problems will be both numerical and essay, with occasional true/false, fill in the blank, or multiple choice.

Course Outline :

 

08/22

(Week 1) Introduction and overview, Why Statistics?

08/29

(2) Decision Making (Material provided from Raiffa)

09/05

(3) Decision Making

09/12

(4) Introduction to statistical thinking

09/19

(5) Midterm 1, go over midterm

09/26

(6) Descriptive Statistics Chapter 1. Probability Chapter 2

10/03

(7) Distributions Chapters 3 and 4

10/10

(8) Confidence, sampling and decision making Chapters 5,8 and 9

10/27

(9) Confidence, sampling and decision making Chapters 5,8 and 9

10/24

(10) Prediction Chapter 12

10/31

(11) Review and midterm 2

11/07

(12) Go over midterm, Experimentation and Analysis, Chapter 10 and 11

11/14

(13) Experimentation and Analysis, Chapter 10 and 11

11/21

(14) Interpretation

11/28

(15) Review

12/12

Final 8:00 A.M. – 10:00 A.M.

 

Expectations: 

Students are expected to attend every session, be on time, to have read the preparation material and participate actively in the discussions in the class. The use of laptops, I phones or similar devices during class is discouraged. Students are also expected to post comments and questions on the discussion board (or send emails or contributions to be used in class). You should be prepared to devote the time necessary to take the course. The course material is cumulative and you need to keep up as we go along. 

Method of Instruction:

Class sessions will generally consist of quizzes and their solution, going over homework, assigning new homework, questions and answers, lecture, and discussion.

ALWAYS BE SURE TO GIVE THE SOURCE OF ALL YOUR INFORMATION. ANYTHING TAKEN VERBATIM FROM SOMEONE ELSE MUST BE IN QUOTATION MARKS AND REFERENCED. THIS INCLUDES PARTIAL SENTENCES.
This is intended to be an interactive class and your participation should increase as the semester progresses. Attendance at all classes is expected of everyone. Frequent absences will result in a reduction in grade. Punctuality is expected. If you are late, be sure not to disturb the class as you enter.

PLEASE DO NOT BRING FOOD OR DRINKS TO THE CLASS. (Water in plastic bottles is OK)
The midterms and final will be based on problems similar to the ones assigned in the homework and the discussions in class. All tests are open book and open notes. Laptops are also allowed. Students are expected to apply what they should have learned up to that point to analyzing situations, identifying the problems and applying the appropriate techniques to solve them.

NEATNESS, SPELLING, AND GRAMMAR COUNT. THEY ARE AN EXPRESSION OF YOUR COMMITMENT TO DO A GOOD JOB.

Last, but most important:
Academic Conduct
Plagiarism – presenting someone else’s ideas as your own, either verbatim or recast in your own words – is a serious academic offense with serious consequences.  Please familiarize yourself with the discussion of plagiarism in SCampus in Section 11, Behavior Violating University Standards https://scampus.usc.edu/1100-behavior-violating-university-standards-and-appropriate-sanctions.  Other forms of academic dishonesty are equally unacceptable.  See additional information in SCampus and university policies on scientific misconduct, http://policy.usc.edu/scientific-misconduct.

Discrimination, sexual assault, and harassment are not tolerated by the university.  You are encouraged to report any incidents to the Office of Equity and Diversity http://equity.usc.edu  or to the Department of Public Safety http://capsnet.usc.edu/department/department-public-safety/online-forms/contact-us.  This is important for the safety of the whole USC community.  Another member of the university community – such as a friend, classmate, advisor, or faculty member – can help initiate the report, or can initiate the report on behalf of another person.  The Center for Women and Men http://www.usc.edu/student-affairs/cwm/ provides 24/7 confidential support, and the sexual assault resource center webpage http://sarc.usc.edu describes reporting options and other resources.

Support Systems

A number of USC’s schools provide support for students who need help with scholarly writing.  Check with your advisor or program staff to find out more.  Students whose primary language is not English should check with the American Language Institute http://dornsife.usc.edu/ali, which sponsors courses and workshops specifically for international graduate students.  The Office of Disability Services and Programs http://sait.usc.edu/academicsupport/centerprograms/dsp/home_index.html provides certification for students with disabilities and helps arrange the relevant accommodations.  If an officially  declared emergency makes travel to campus infeasible, USC Emergency Information http://emergency.usc.eduwill provide safety and other updates, including ways in which instruction will be continued by means of blackboard, teleconferencing, and other technology.