Causal methods causal methods linear regression

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Causal Methods Causal Methods Linear Regression Linear Regression Sales, Sales, Y Advertising, Advertising, X Month Month (000 units) (000 units) (000 $) (000 $) XY XY X X 2 Y Y 2 1 264 264 2.5 2.5 660.0 660.0 6.25 6.25 69,696 69,696 2 116 116 1.3 1.3 150.8 150.8 1.69 1.69 13,456 13,456 3 165 165 1.4 1.4 231.0 231.0 1.96 1.96 27,225 27,225 4 101 101 1.0 1.0 101.0 101.0 1.00 1.00 10,201 10,201 5 209 209 2.0 2.0 418.0 418.0 4.00 4.00 43,681 43,681 a a = = Y Y b b X X b b = = XY XY n n XY XY X X 2 2 n n X X 2 2
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Causal Methods Causal Methods Linear Regression Linear Regression Sales, Sales, Y Advertising, Advertising, X Month Month (000 units) (000 units) (000 $) (000 $) XY XY X X 2 Y Y 2 1 264 264 2.5 2.5 660.0 660.0 6.25 6.25 69,696 69,696 2 116 116 1.3 1.3 150.8 150.8 1.69 1.69 13,456 13,456 3 165 165 1.4 1.4 231.0 231.0 1.96 1.96 27,225 27,225 4 101 101 1.0 1.0 101.0 101.0 1.00 1.00 10,201 10,201 5 209 209 2.0 2.0 418.0 418.0 4.00 4.00 43,681 43,681 Total Total 855 855 8.2 8.2 1560.8 1560.8 14.90 14.90 164,259 164,259 Y = 171 = 171 X = 1.64 = 1.64 n XY XY X X Y [ n X X 2 – ( – ( X ) ) 2 ][ ][ n Y Y 2 – ( – ( Y ) ) 2 ] r r = =
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Selection of Forecasting Techniques Principle of Forecasting : * When past data are known as good indicator for the future. * The pattern of the future can be recognized from the past data. Qualitative Techniques are used when: * Data unavailable * Unknown pattern change
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Selection of Forecasting Techniques (II) Quantitative Techniques: A. Time series models: use when past demand is the best indicator for future demand. B: Causal relationship model: used when the demand of an item is dependent on other underlying factors.
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Practical Forecasting Problems 1. Practical forecasting issues: * Inaccuracy * Inconsistency * Cost and accuracy tradeoff * Data unavailability * fitness and predictability “A model that best fits the past data may not be the best predictive one for the future due to demand pattern changes.”
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Criteria for Selecting a Forecasting Method Cost and accuracy Data available Time span Nature of products and services Impulse response and noise dampening
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Practical Forecasting Problems 2. new direction in forecasting: * integrated forecasting system: to reduce inconsistency * Combination forecasting models: To reduce inaccuracy through: ---model combinations ---result combinations
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Forecasting with Computers Forecasting software packages are widely available Three categories Manual systems Semiautomatic systems Automatic systems Package selection depends on: Fit with musts and wants Costs of the package Level of clerical support required, and Amount of programmer maintenance required
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See Guidelines for Using <POM – Windows> Software for Forecasting Problems.
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Written Assignment - is due …..
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