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Statistics  for Management  Lesson 7 Time-Series Analysis
Lesson Topics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
What Is Time-Series  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
1. Time-Series Components Time-Series Cyclical Random Trend Seasonal
Trend Component ,[object Object],[object Object],Sales Time  Upward trend
Cyclical Component ,[object Object],[object Object],[object Object],Sales Time  Cycle
Seasonal Component ,[object Object],[object Object],[object Object],Sales Time (Monthly or Quarterly)  Winter
Random or Irregular Component ,[object Object],[object Object],[object Object],[object Object],[object Object]
Multiplicative  Time-Series Model ,[object Object],[object Object],[object Object],[object Object],T i   = Trend C i   = Cyclical I i   = Irregular S i   = Seasonal
2. Moving Averages ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Moving Average Example Year  Units   Moving   Ave 1994   2  NA 1995   5   3  1996   2   3 1997   2   3.67 1998   7  5 1999   6  NA John is a building contractor with a record of a total of 24 single family homes constructed over a 6 year period.  Provide John with a Moving Average Graph.
Moving Average Example Solution Year   Response  Moving   Ave 1994   2   NA 1995   5   3  1996   2   3 1997   2   3.67 1998   7   5 1999   6   NA 94  95  96  97  98  99 8 6 4 2 0 Sales
3. Exponential Smoothing ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Exponential Weight: Example Year   Response  Smoothing Value   Forecast (W = .2)   Ei 1994   2     2   NA 1995   5   (.2)( 5 ) + (.8)(2) = 2.6   2 1996   2   (.2)( 2 ) + (.8)(2.6) = 2.48  2.6 1997   2   (.2)( 2 ) + (.8)(2.48) = 2.384  2.48 1998   7   (.2)( 7 ) + (.8)(2.384) = 3.307  2.384 1999   6   (.2)(6) + (.8)(3.307) = 3.846   3.307
Exponential Weight: Example Graph 94  95  96  97  98  99 8 6 4 2 0 Sales Year Data Smoothed
4. The Linear Trend Model Year  Coded  Sales 94   0  2 95   1  5 96   2  2 97   3  2 98   4  7 99   5  6 Projected to year 2000
The Quadratic Trend Model Year  Coded  Sales 94   0  2 95   1  5 96   2  2 97   3  2 98   4  7 99   5  6
The Exponential Trend Model or Excel Output of Values in logs Year  Coded  Sales 94   0  2 95   1  5 96   2  2 97   3  2 98   4  7 99   5  6
5. Autogregressive Modeling ,[object Object],[object Object],[object Object],[object Object],[object Object],Random Error
Autoregressive Model: Example The Office Concept Corp. has acquired a number of office units (in thousands of square feet) over the last 8 years. Develop the 2nd order Autoregressive models. Year  Units   92   4 93   3 94  2   95  3  96   2  97   2  98   4 99   6
Autoregressive Model: Example Solution Year   Y i   Y i-1   Y i-2 92   4   ---  --- 93   3   4  --- 94  2   3  4 95  3   2  3 96  2  3   2 97   2  2  3 98   4  2  2 99   6  4  2 ,[object Object],[object Object]
Autoregressive Model Example: Forecasting Use the 2nd order model to forecast number of units for 2000:
Autoregressive Modeling Steps ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
6. Selecting A Forecasting Model ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Measuring Errors ,[object Object],[object Object]
Principal of Parsimony ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lesson Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Lesson08_new

  • 1. Statistics for Management Lesson 7 Time-Series Analysis
  • 2.
  • 3.
  • 4. 1. Time-Series Components Time-Series Cyclical Random Trend Seasonal
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11. Moving Average Example Year Units Moving Ave 1994 2 NA 1995 5 3 1996 2 3 1997 2 3.67 1998 7 5 1999 6 NA John is a building contractor with a record of a total of 24 single family homes constructed over a 6 year period. Provide John with a Moving Average Graph.
  • 12. Moving Average Example Solution Year Response Moving Ave 1994 2 NA 1995 5 3 1996 2 3 1997 2 3.67 1998 7 5 1999 6 NA 94 95 96 97 98 99 8 6 4 2 0 Sales
  • 13.
  • 14. Exponential Weight: Example Year Response Smoothing Value Forecast (W = .2) Ei 1994 2 2 NA 1995 5 (.2)( 5 ) + (.8)(2) = 2.6 2 1996 2 (.2)( 2 ) + (.8)(2.6) = 2.48 2.6 1997 2 (.2)( 2 ) + (.8)(2.48) = 2.384 2.48 1998 7 (.2)( 7 ) + (.8)(2.384) = 3.307 2.384 1999 6 (.2)(6) + (.8)(3.307) = 3.846 3.307
  • 15. Exponential Weight: Example Graph 94 95 96 97 98 99 8 6 4 2 0 Sales Year Data Smoothed
  • 16. 4. The Linear Trend Model Year Coded Sales 94 0 2 95 1 5 96 2 2 97 3 2 98 4 7 99 5 6 Projected to year 2000
  • 17. The Quadratic Trend Model Year Coded Sales 94 0 2 95 1 5 96 2 2 97 3 2 98 4 7 99 5 6
  • 18. The Exponential Trend Model or Excel Output of Values in logs Year Coded Sales 94 0 2 95 1 5 96 2 2 97 3 2 98 4 7 99 5 6
  • 19.
  • 20. Autoregressive Model: Example The Office Concept Corp. has acquired a number of office units (in thousands of square feet) over the last 8 years. Develop the 2nd order Autoregressive models. Year Units 92 4 93 3 94 2 95 3 96 2 97 2 98 4 99 6
  • 21.
  • 22. Autoregressive Model Example: Forecasting Use the 2nd order model to forecast number of units for 2000:
  • 23.
  • 24.
  • 25.
  • 26.
  • 27.