Statistics for Decision Making

1
Statistics for Decision Making
QM 2113 -- Fall 2003

• Exam 2 and In-Class Excel Exercise

Instructor John Seydel, Ph.D.
2
Student 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

3
Exam 2

• Name top right portion of exam
• Work
• On exam (in space provided or on flip side)
• Manual calculations
• Discussion where warranted
• On Excel output (save file)
• Relevant info only dont print data!
• Fit to 1 page (worksheet) per problem
• Print grid lines and row/column labels
• Other
• Closed book / closed notes / open website
• Data available from the Handouts page
• After the exam
• Turn-in exam and relevant Excel output (stapled)
• Return to BU 201 (this lab)
• Read The Gaming Company case
• Download data file

4
The Gaming Company Overview

• Time series data
• A basic inventory decision (2 decisions
  controllable inputs)
• How much to order (same quantity each time)?
• When (i.e., the reorder point)?
• Information (uncontrollable inputs)
• What do we need to know?
• What do we know?
• How might that be helpful?
• Refer to Exhibit 3
• Some limitations
• Ordering takes place each Monday morning
• Goods arrive Sunday following
• Use the same order quantity for all orders
• Cant make up unmet demand (i.e., no backorders)

5
The Gaming Company Working with Excel

• Two phases data analysis decision worksheet
• Data analysis
• 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 . . .

6
Gaming Company Decision Worksheet

• Based upon Exhibits 2 3
• Demonstrates
• Excel functions
• SUM
• IF
• MAX
• Absolute versus relative references
• Copying cells
• Naming cells
• Using AutoFill
• Playing What-If
• Manually need to keep track of what-if results

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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

8
Appendix
9
Recall Data Type Is Very Important

• Type of analysis depends upon data
• Quantitative youll also see these terms
• Ratio
• Interval
• Ordinal
• Qualitative youll also see these terms
• Ordinal
• Nominal
• General classifications of data
• 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

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Sampling
Population (or Process)
Sample
Statistic
Parameter