# hw4 - R-squared = 88.6823 percent R-squared(adjusted for...

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Alfredo Castillo 11-09-10 DS 101: HW #4 Multiple Regression - Sales Dependent variable: Sales Independent variables: Advertising Price Winter Spring Summer Standard T Parameter Estimate Error Statistic P-Value CONSTANT 72608.9 7973.76 9.10599 0.0000 Advertising 13.0117 0.843562 15.4248 0.0000 Price -1855.63 304.56 -6.09281 0.0000 Winter 7948.93 1425.32 5.57695 0.0000 Spring -629.373 1475.57 -0.426528 0.6716 Summer 4908.38 1476.99 3.32323 0.0017 Analysis of Variance Source Sum of Squares Df Mean Square F-Ratio P-Value Model 5.43152E9 5 1.0863E9 78.36 0.0000 Residual 6.93173E8 50 1.38635E7 Total (Corr.) 6.12469E9 55

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Unformatted text preview: R-squared = 88.6823 percent R-squared (adjusted for d.f.) = 87.5506 percent Standard Error of Est. = 3723.37 Mean absolute error = 2725.04 Durbin-Watson statistic = 1.94373 (P= 0.4375 ) Lag 1 residual autocorrelation = 0.0140627 Component+Residual Plot for Sales 800 120016002000240028003200 Advertising-19-9 1 11 21 (X 1000.0) component effect Sales = 72608.9 + 13.0117*Advertising - 1855.63*Price + 7948.93*Winter - 629.373*Spring + 4908.38*Summer Advertising: Price: Winter: Spring: Summer:...
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## This note was uploaded on 11/17/2010 for the course MGMT 3620 taught by Professor Ryan during the Spring '10 term at California State University , Monterey Bay.

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hw4 - R-squared = 88.6823 percent R-squared(adjusted for...

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