STA302H1 Lecture Notes - Lecture 22: Analysis Of Variance
Document Summary
> model1=lm(salesthisquarter~saleslastquarter + c1 + c2 + c1*saleslastquarter + c2*saleslastquarter) Call: lm(formula = salesthisquarter ~ saleslastquarter + c1 + c2 + c1 * saleslastquarter + c2 * saleslastquarter) Error t value pr(>|t|) (intercept) -44. 1497 21. 3607 -2. 067 0. 04747 * Saleslastquarter 1. 5883 0. 2865 5. 543 5. 02e-06 *** c1 -48. 1097 29. 6808 -1. 621 0. 11550 c2 96. 5419 32. 3965 2. 980 0. 00567 ** Error t value pr(>|t|) (intercept) -38. 7664 14. 8864 -2. 604 0. 0136 * Residual standard error: 6. 944 on 34 degrees of freedom. F-statistic: 62. 28 on 1 and 34 df, p-value: 3. 436e-09. Model 1: salesthisquarter ~ saleslastquarter + c1 + c2 + c1 * saleslastquarter + c2 * saleslastquarter. Res. df rss df sum of sq f pr(>f) > reduced1=lm(salesthisquarter~saleslastquarter + c1 + c3 + c1*saleslastquarter + c3*saleslastquarter) Call: lm(formula = salesthisquarter ~ saleslastquarter + c1 + c3 + c1 * saleslastquarter + c3 * saleslastquarter) Error t value pr(>|t|) (intercept) 52. 3922 24. 3568 2. 151 0. 03965 *
