# Forecasting

Document Sample

```					Forecasting

5 June 2001
Introduction
   What: Forecasting Techniques
   Where: Determine Trends
   Why: Make better decisions
What is Forecasting?
   The art and science of predicting future
events
Time Horizon
   Short Range – 3 – 12 months
   Medium Range – 3 months – 3 years
   Long Range – 3+ years
Qualitative Methods
   Jury of Executive Opinion
   Sales Force Composite
   Delphi
   Consumer Marketing Survey
Quantitative Methods
   Time Series
   Associative
Time Series Methods
   Trend
   Seasonality
   Cycle
   Random Variations
Naïve Approach
Moving Average Approach

MA   Demand in Previous n Periods
n
Weighted Moving Average

Σ(Weight for period n) (Demand in period n)
WMA =
ΣWeights
Exponential Smoothing
   Ft = Ft-1 + (At-1 - Ft-1)

 forecast errors
n
MSE
Exponential Smoothing With
Ft = (At) + (1- )Ft-1 + Tt-1

Tt = (Ft - Ft-1) + (1- )Tt-1
Linear Trend Projection
Equation:      ˆ
Yi  a  bx i

n
 x i y i  nx y
Slope:           b  i 
n

 x i  nx 
i 

Y-Intercept:      a  y  bx
Seasonal Variations
Regression Analysis

Equation:      ˆ
Yi  a  bx i
n
 x i y i  nx y
Slope:           b  i 
n

 x i  nx 
i 

Y-Intercept:      a  y  bx
Standard Error of Estimate

n
   yi  yi 
ˆ
S y,x  i 
n

n        n        n
 yi  a  yi  b  x i yi
   i       i      i 
n
Correlation Coefficient

```
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
 views: 21 posted: 8/31/2012 language: English pages: 19