Estimating Demand Chapter 4. A chief uncertainty for managers is the future. Managers fear what will happen to their product. Managers use forecasting, prediction & estimation to reduce their uncertainty.
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Is this curve demand
t = Yt - a - b Xt
t2 = [Yt - a - b Xt] 2 .
slope b = Cov(Y,X)/Var(X)and
intercept a = mean(Y) - b•mean(X)
One use of a regression is to make predictions.
RULE: If absolute value of the estimated t>Critical-t, then REJECT Ho.
Y = 120.755 + .434 X
Dep var: Sales (Y) N=10 R-squared = .790
Adjusted R2 = .684 Standard Error of Estimate = 17.417
Variable Coefficient Std error T P(2 tail)
Constant 310.245 95.075 3.263 .017
PromExp .008 0.204 0.038 .971
SellPrice -12.202 4.582 -2.663 .037
DispInc 2.677 3.160 0.847 .429
Analysis of Variance
Source Sum of Squares DF Mean Squares F p
Regression 6829.8 3 2276.6 7.5 .019
Residual 1820.1 6 303.4
Sales = 310.245 + .008 ProExp -12.202 SellPrice + 2.677 DispInc
Linear estimation yields:
Cans = 159.17-102.56 Price +1.00 Income + 3.94 Temp
Linear Specification write as an equation: