Elon
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| This course introduces the student to a systematic approach to problem
solving and decision making through the application of selected quantitative
models and statistical methods. The intent is for the student to gain an
appreciation of the power of formal models and statistical tools through
their application in a variety of decision making environments.
The purpose of statistics and decision making in a business setting
is to make meaningful statements about an issue based on limited information.
The course highlights the importance of determining the type of data and
the type of problem that is being investigated prior to choosing and developing
the decision making tool to be applied. We will develop and apply the useful
tools of estimation, ordinary least squares regression, and decision making.
We will emphasize the application of these techniques to management problems
in order to help businesses make better decisions. To develop a strong
applications approach, the computer spreadsheet package EXCEL will be used
in conjunction with the text. We will also develop an understanding of
when it is appropriate to apply a specific technique.
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Upon completion of this course you should be able to:
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| Problems/Discussion: Problems will be assigned from the text
and from outside sources. Problems will be done both long-hand and
with calculators/computers. Some problems will be handed in and others
will be done by you in-class. I
recommend you find a “study buddy.” Some of the work will allow pairs or 3-tuples. Memos: There will be two memos concerning descriptive statistics and probability generated using data from your place of employment. They will each be worth 10% of your grade. Midterm: The midterm will be due on the 5th class meeting. It will be a take-home exam, containing problems similar to those done in class for homework, and might entail some computer work. Paper: The paper will be a description and analysis of a data set which you will generate from your place of employment. It will include both computer work and a description of the methods used, as well as any conclusions you might reach that would be beneficial to your employer. More detailed information will be provided later. Final Exam: There will be a “cumulative” final due the last day
of class. The final will mainly be a take-home exam, but will include
a couple of in-class problems.
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| Class Hours: T,R 6:00 – 9:00 p.m. L-114
Office Hours: Before and after class or by appointment. Or e-mail me questions at redingto@elon.edu |
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Grading and Evaluation:
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| Required Text: Anderson, Sweeney and Williams: Statistics for
Business and Economics, 7th, 1999
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| Tentative Coverage:
7/8 Introduction, algebraic optimization, linear programming
7/13 Probability (Ch. 4, 5)
7/15 Continuous probability (Ch. 6)
7/20 Sampling and sampling distributions (Ch. 7, 21)
7/22 Sampling (cont’d) and general introduction to estimation 7/27 Regression analysis (Ch. 14, 15)
7/29 Regression (cont’d) and continued intro to estimation 8/3 Statistical decision making (Ch. 8, 9, 10, 20)
8/5 Model building (Ch. 16) and wrap-up
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