Time YearQ Quarterin million MODEL 1: Y= + A Period +5, D1 + ?. D2 +5, D3 2004 W

Question

Time YearQ Quarterin million MODEL 1: Y= + A Period +5, D1 + ?. D2 +5, D3 2004 Winter35.452 Spring 41.4892 Summer S40.9823 SUMMARY OUTPUT Recreesion Statistics Multiple R 0.9097 R Square 0.8278 Adi. R Sq 0.7849 St. Error 8.4940 S 42.777 2005 Winter43.492 Spring $57.6898 Summer $59.478 78.909 2008 Winter 3103 SpringS84.458 Summer 67.990 S 88.543 12 2007 Winter 73.457 13 Spring 89.12414 Summer 85.892 15 Reressio 13.20 0004 4 3808.97 95224 11 793.83 7215 2 Coef.SError tStat P-value Intercept 5.03 0.0004 883 0.0000 0.14 08930 1.68 0.1212 32.04 8.37 .24 0.47 0.85 MODEL 2: Y B + ? Period + ?2 D2 + ?, D3 MODEL 3: Y= + B Period + ?,02 SUMMARY SUMMARY OUTPUT Multiple R R Square Adj. R Sq. 0.9095 0.8273 0.7841 8.1394 Multiple R 0.9071 R Square0.8228 Adj. R Sq. 0.7955 St Eror7.9216 ANOVA ANOVA 19.16 0.0001 2 3788.83 1893.42 30.17 0.0000 13 815.76 62.75 Regressio 3 3807.60 1289.20 88.25 Res idual 12 795.00 15 480 Inter cept Period 6.85 0.0000 7.38 0.0000 213 0.0542 Intercept Period 7.39 0.0000 759 0.0000 4.58 2.120.0537 31.48 10.85

Explanation / Answer

1. Null hypothesis: The coefficients of the explanatory variables are zero and the model can't predict the values.

2. Avg. increase in sales per quarter can be determined from the coefficient of the variable 'period'. Hence, the average increase in sales per quarter is 3.24 million.

3. Based on the models we can say that the seasons have the following sales: (approximate values)

Spring: 10.21

Summer: 2.4

Fall: 0

Winter: -0.85

But only the p-value of Spring season is significant. Hence, we can say that:

The order is Spring>Summer=Fall=Winter

4. Model 3 equation:

y = 32.32 + 3.27 (Period) + 9.72 (D2)

For Spring 2008, D2 = 1, Period = 18

Hence, y = 32.32 + 3.27*18 + 9.71*1

y = 100.89 million

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