2. Statistics for Decision Making Exam #2 and In-Class Excel Exercise Instructor: John Seydel, Ph.D. QM 2113 -- Fall 2003

3. 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

4. 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; don’t 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

5. The Gaming Company: Overview Time seriesTime 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 #3Exhibit #3 Some limitations: 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)

6. 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...

7. 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

8. 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

9. Appendix

10. Type of analysis depends upon data: Quantitative; you’ll also see these terms  Ratio  Interval  Ordinal Qualitative; you’ll 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 Recall: Data Type Is Very Important

11. Sampling Population (or Process) Sample Parameter Statistic