Stat 5802 Syllabus – Spring 2010
(Last modified – 12/14/2009. This syllabus is subject to change)
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Instructor Dr.
Howard J. Weiss 215-204-6829 Home: 215-572-6388 (not after
9:30 please) I respond best to email. I will respond to emails and voice-mails as quickly as possible. Most times with email, the response will be within 1 hour but I can not promise a response time of less than 12 hours especially on weekends. When
you send any professor email be sure to include the following items. 1.
Your
name (you should set up a signature in your email program) 2.
Your
class (Stat 5802) 3. Any previous email that was sent on the same topic. In particular, if you are replying to an email be sure to include the original email. 4. If the email refers to a problem you are having with a homework problem then please attach a file with the problem.
Please note that it is generally considered rude to send email that is all CAPS. CAPS IS THE EMAIL VERSION OF SHOUTING |
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Course name and number Statistics 5802: Quantitative Techniques for Management |
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Prerequisites Statistics 5801 |
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Disability disclosure
statement Any student who has a need for accommodation based on the impact of a disability should contact me privately to discuss the specific situation as soon as possible. Contact Disability Resources and Services at 215-204-1280 in 100 Ritter Annex to coordinate reasonable accommodations for students with documented disabilities. (from Policy on Course Syllabi, #02.78.13 |
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Student and Faculty Academic Rights and Responsibilities Freedom to teach and freedom to learn are
inseparable facets of academic freedom. The University has adopted a policy
on Student and Faculty Academic Rights and Responsibilities (Policy #
03.70.02) which can be accessed through the following link: http://policies.temple.edu/getdoc.asp?policy_no=03.70.02. (from Policy on Course Syllabi, #02.78.13) |
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Class
Meeting Times Fridays & Saturdays, 8:00 – 10:30. See schedule below for dates. |
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Course Goals We study advanced
quantitative techniques that are routinely used for managerial decision
making. This includes time series models and forecasting. Other probabilistic
models discussed include decision analysis, simulation and Markov chains. In
addition deterministic models including linear, and integer programming,
transportation, networks and game models are discussed. The goal of this course
is to provide students with a description of these models and their
applications. The emphasis is on the modeling process rather than on the
solution process. Software packages will be used to solve problems and
interpretation of the model inputs, outputs and assumptions will be
thoroughly examined.
A secondary goal of this course is to improve students’ Excel skills. |
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Learning materials and supplies Texts Quantitative
Analysis for Management, 10th
edition by Render, Stair and Hanna, Prentice-Hall, 2009 Note: The text should be treated as a supplement. I will present the bulk of the modeling and interpretation in class. You should skim the chapters in the text prior to class paying attention to the modeling aspects but for the most part ignoring the computational aspects. Software Excel - In addition to using Excel's normal spreadsheet
capabilities we will also be using two of its add-ins - Data Analysis and
Solver. Please be sure that Solver and Data analysis are installed in your
Excel. Both of these options should appear in the Analysis section on the far
right of the Data Tab in Excel 2007. In addition, the following packages that are the most recent versions of the ones on the CD that accompanies the text will be provided to you..
1.
POM-QM for Windows,
Version 3 by Howard J. Weiss,
Prentice-Hall, 2006. 2. Excel QM, v3 by Howard J. Weiss, (Prentice-Hall), 2006. This is an add-in for Excel that generates spreadsheets for models in quantitative methods.
The last software package that will be used is Crystal Ball. This is an add-in for Excel which is used for simulation. Journal Interfaces, which can be accessed through the Temple University
Library web site is the journal that
publishes papers on the practice and implementation of quantitative
(operations research/management science) models. |
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Academic requirements Examinations One team, take-home
examination and one individual, in-class examination will be given. The
in-class examination will count 20% towards the grade while the
team-take-home exam will count 15% towards the grade.
The take-home examination
is posted on our course
web page. It is a team exam to be done by each
of the study groups. I expect all members of the team to participate in the
examination. The examination due date is on the week-by-week schedule at the
end of this document. Late examinations will not be accepted.
One in-class
examination will be given and the computer will be required for this exam.
The examination will be designed to ensure that students understand the modeling
process, the assumptions of the different models and the implications of the
results of these models. The examination will cover all topics from
Render/Stair/Hanna discussed in the course. The examination date is on the
week-by-week schedule at the end of this document. Forecasting Application Each student will obtain a time-series data set (of at least 4 full cycles) from his or her place of employment that will be used for analysis. The data set might likely be demand but is not restricted to demand. This data set is to be fully analyzed using appropriate forecasting and Excel graphing techniques. The requirements for the paper will be further discussed at our first or second class. The forecasting application due date is on the week-by-week schedule at the end of this document. The project will count 20% towards the final grade.
Linear Programming Interpretations You are to perform a complete
analysis of the results for two linear programming problems that will be
assigned. One will be an individual assignment and the other will be a team
assignment. Each analysis will count 10% towards the course grade. The
linear program interpretation due dates are on the week-by-week schedule at
the end of this document. Decision Tree Each team will be
required to create and analyze a decision tree. The Decision Tree will count
7.5% towards the final grade Simulation Application We will have a team Crystal Ball exercise that will count 7.5% towards the final grade. I am hoping to give the exercise in class but it may be given as a take home exercise. Homework Homework will be
assigned weekly. Problems are due prior to the next class weekend unless
stated otherwise. Homework will not be collected. Some problems will be
reviewed in class. I encourage you to interact with your classmates when
doing the homework. You can work together by phone, fax or modem if not in
person. Feel free to send questions about the homework to the listserv. Application paper based on Interfaces Interfaces
is the journal that publishes papers on the practice and implementation of
quantitative (operations research/management science) models. The journal is
available on-line through the
Instructions for finding the article are given in the homework assignment to be completed over the winter break. The first presentations will be due on January 17. The Interfaces paper and presentation will count 10% towards the final grade. |
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Attendance Role will in general not be taken. Any student missing a class will penalize himself/herself as he/she will miss the instructor's pearls of wisdom. Class begins promptly at 8:00. It is both rude and disruptive to walk in late. |
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Grading Grades The grades
will be based on the following:
For the team projects I will take into consideration your teammates’ evaluations of your work when assigning individual grades. I expect full participation from all team members on all team projects. Academic Honesty Any student suspected
of cheating will be brought up to the university disciplinary committee. The
following information is from the Code of Conduct site at http://www.temple.edu/grad/policies/. Cheating includes
falsifying data; submitting, without the instructor's approval, work in one
course which was done for another; helping others to plagiarize or cheat from
one's own or another's work; or actually doing the work of another person. The penalty for
academic dishonesty can vary from a reprimand and receiving a failing grade
for a particular assignment, to a failing grade in the course, to suspension
or expulsion from the University. For more information
concerning disciplinary and/or academic grievance procedures, contact the |
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Office hours I am available before and after class for office hours. In addition, I am available by phone or email or by appointment. |
Course schedule (subject to change)
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Week |
Chapter |
Topic |
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(Sunday,
January 10) |
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Forecasting data due by email – 8pm Interfaces paper information due by email by
8pm Software packages should be installed and
tested |
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Friday, January 15 (10:45-2:15) |
5 |
Forecasting – Error measures, time series, simple regression |
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Saturday, January 16 |
5 |
Forecasting - Multiple regression, seasonality,
tracking Analyses of your project data n class |
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(Sunday,
January 24) |
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Forecasting project should be completed.
Give draft to teammates, significant others, colleagues for review!!! |
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Saturday, January 30 |
7 |
Forecasting project due – 8am Linear Programming - Model Formulation |
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(Sunday, February 7) |
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Individual linear programming interpretation is due (by
email by 8pm) |
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Friday, February 12 |
8 10 |
Linear Programming – Formulating problems in
Excel Transportation and Assignment Models |
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Saturday, February 13 |
11 |
Integer Programming Models |
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(Sunday,
February 21) |
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Team linear programming interpretation is due
(by email by 8pm) |
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Saturday, February 27 |
3 |
Decision Tables & Decision Trees |
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(Sunday, March 7) |
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Team decision tree project due – 8pm |
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March 7 – 13 |
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SPRING BREAK |
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Saturday March 20 |
12, 16 |
Network Models, Markov Chains |
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(Sunday, March 28) |
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Friday, April 2 |
15 |
Simulation |
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Saturday, April 3 |
15 |
Simulation & Crystal Ball Team
simulation project – possibly in-class, possibly at home |
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(Sunday, April 11) |
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Team take home examination due (by email by
8pm) |
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Friday April 16 |
CD Module 1 |
Analytic Hierarchy Process, Guest Lecture, Dr. Robert L. Nydick |
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Saturday April 17 |
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In class examination |
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(Saturday, April 24) |
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Snow Emergency Make-up Day |
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Saturday, May 1 |
CD Module 4 |
Game models & Summary of course |
Note: There
are no classes for the dates shaded and in italics.