Download Exam #2 and In-Class Exercise

QM 2113 -- Fall 2003
Statistics for Decision Making
Exam #2 and In-Class Excel Exercise
Instructor: John Seydel, Ph.D.
Student Objectives
Demonstrate knowledge of
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Univariate descriptive statistics
Bivariate descriptive statistics
Informal inference procedures
Normal probability distribution concepts and
applications
Excel support for descriptive data analysis
Use Excel to perform elementary analysis of
time series data
Develop Excel worksheets that incorporate
decision logic
Exam #2
Name: top right portion of exam
Work:
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On exam (in space provided or on flip side)
 Manual calculations
 Discussion where warranted
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On Excel output (save file)
 Relevant info only; don’t print data!
 Fit to 1 page (worksheet) per problem
 Print grid lines and row/column labels
Other:
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Closed book / closed notes / open website
Data: available from the Handouts page
After the exam:
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Turn-in exam and relevant Excel output (stapled)
Return to BU 201 (this lab)
Read “The Gaming Company” case
Download data file
The Gaming Company: Overview
Time series data
A basic inventory decision (2 decisions: controllable inputs)
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How much to order (same quantity each time)?
When (i.e., the reorder point)?
Information (uncontrollable inputs)
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What do we need to know?
What do we know?
How might that be helpful?
Refer to Exhibit #3
Some limitations:
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Ordering takes place each Monday morning
Goods arrive Sunday following
Use the same order quantity for all orders
Can’t make up unmet demand (i.e., no backorders)
The Gaming Company: Working
with Excel
Two phases: data analysis & decision
worksheet
Data analysis
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Variable is: weekly demand (# of cases)
Determine
 Basic descriptive statistics
 Histogram (note: discrete variable)
 Time series (XY) plot: demand versus time

How might this be of help with the decision
making?
Decision worksheet . . .
Gaming Company: Decision
Worksheet
Based upon Exhibits 2 & 3
Demonstrates:
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Excel functions
 SUM
 IF
 MAX
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Absolute versus relative references
Copying cells
Naming cells
Using AutoFill
Playing “What-If”
Manually: need to keep track of “what-if”
results
Summary of Objectives
Demonstrate knowledge of





Univariate descriptive statistics
Bivariate descriptive statistics
Informal inference procedures
Normal probability distribution concepts and
applications
Excel support for descriptive data analysis
Use Excel to perform elementary analysis of
time series data
Develop Excel worksheets that incorporate
decision logic
Appendix
Recall: Data Type Is Very
Important
Type of analysis depends upon data:
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Quantitative; you’ll also see these terms
 Ratio
 Interval
 Ordinal
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Qualitative; you’ll also see these terms
 Ordinal
 Nominal
General classifications of data
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Information content
Source
Time frame: cross-sectional (e.g., WNB data) or time series
(e.g., Gaming Company)
Time series analysis: a form of univariate analysis
Sampling
Population (or Process)
Sample
Statistic
Parameter