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Ch 4 - Forecasting
(Covered in DS 2334 - Business and Economic Statistics II)

  1. Introduction
    1. Def - Forecasting - the art and science of predicting future events
    2. Types of Forecasts (p107)
      1. Economic
      2. Technological
      3. Demand
    3. Forecasting Methods (p108)
      1. Qualitative Methods
             Jury of Executive Opinion 
             Delphi Method
             Sales Force Composite
             Consumer Market Survey
      2. Quantitative Methods
             Time Series Methods
             Regression Methods - Simple Linear, Multiple Linear
  2. Simple Linear Regression   (p128)
    1. Variables
              y - dependent,   x – independent
    2. Linear relationship
              yf = a+bx
              (Estimate a, b using least squares)
    3. Nodel Construction - p129 - renovates homes
              y - sales (in $ millions)
              x - local payroll (in $ billions)
      1. Regression equation, yf = 1.75 + 0.25 x
      2. Forecast when x = 6.0, yf = 1.75 + 0.25 (6.0)
               yf = 3.25 or sales = $3,250,000
  3. Multiple Linear Regression
    1. Variables
              y - dependent,    x1, x2, . . . independent
    2. Linear relationship
              yf = a + b1x1 + b2x2 + . . .
              (Estimate a, b1, b2, . . . using least squares)
    3. Nodel Construction - page 133
              y - sales,     x1 - local payroll, x2 - average annual interest rate
      1. Regression equation, yf = 1.80 + 0.30 x1 - 5.0 x2
      2. Forecast when x1 = 6.0 and x2 = 0.12,
                yf = 1.80 + 0.30 (6.0) - 5.0 (0.12)
                yf = 3.00 or sales = $3,000,000
                            (This page was last edited on January 13, 2010 .)