Lesson 6: Time Series Forecasting

February 8, 2016

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Mon, Feb 8

Review:

• Residual Analysis and R-Squared
• Exam 1

Presentation:

• Forecasting Trend Line
  • Table 12.10 on p. 508
  • Problem 12.48
• Time Series Forecasting (sample data: Crude Oil Prices)
  • Linear Trend
  • Polynomial Curve Fitting
  • Moving Average (MA)
    • Calculate and use as independent (x) variable
    • Develop Linear or Polynomial model based on MA data

Activity:

• Complete Problems 12.49-12.50 on p. 510 (by hand)

Assignment:

• Use Sheets and Crude Oil Price Data to Generate Forecasts (for Oct, Nov, Dec 2015). Develop 3 sets of forecasts using the 4 approaches demonstrated in class: (1) linear trend, (2) polynomial fit and (3) linear and/or polynomial fit using Moving Average data.
• Read p. 504-509, Using Regression to Develop a Forecasting Trend Line
• Read p. 603-606, Intro to Forecasting and Measurement of Forecast Error