require(ggplot2)


> anova(lm(price~table+depth, data = diamonds))
Response: price
             Df     Sum Sq    Mean Sq  F value  Pr(>F)
depth         1 9.7323e+07 9.7323e+07   6.2202 0.01263 *
table         1 1.4462e+10 1.4462e+10 924.2957 < 2e-16 ***
Residuals 53937 8.4391e+11 1.5646e+07

> anova(lm(price~depth+table, data = diamonds))
Response: price
             Df     Sum Sq    Mean Sq F value    Pr(>F)
table         1 1.3876e+10 1.3876e+10 886.825 < 2.2e-16 ***
depth         1 6.8360e+08 6.8360e+08  43.691 3.882e-11 ***
Residuals 53937 8.4391e+11 1.5646e+07

delivery.df = data.frame(
  Service = c(rep("Carrier 1", 15), rep("Carrier 2", 15),
    rep("Carrier 3", 15)),
  Destination = c(rep(c("Office 1", "Office 2", "Office 3",
    "Office 4", "Office 5"), 9)),
  Time = c(15.23, 14.32, 14.77, 15.12, 14.05,
  15.48, 14.13, 14.46, 15.62, 14.23, 15.19, 14.67, 14.48, 15.34, 14.22,
  16.66, 16.27, 16.35, 16.93, 15.05, 16.98, 16.43, 15.95, 16.73, 15.62,
  16.53, 16.26, 15.69, 16.97, 15.37, 17.12, 16.65, 15.73, 17.77, 15.52,
  16.15, 16.86, 15.18, 17.96, 15.26, 16.36, 16.44, 14.82, 17.62, 15.04)
)


> anova(lm(Time ~ Service*Destination, data = delivery.df))
Response: Time
                    Df  Sum Sq Mean Sq  F value    Pr(>F)
Service              2 23.1706 11.5853 161.5599 < 2.2e-16 ***
Destination          4 17.5415  4.3854  61.1553 5.408e-14 ***
Service:Destination  8  4.1888  0.5236   7.3018 2.360e-05 ***
Residuals           30  2.1513  0.0717

> anova(lm(Time ~Destination*Service, data = delivery.df))
Response: Time
                    Df  Sum Sq Mean Sq  F value    Pr(>F)
Destination          4 17.5415  4.3854  61.1553 5.408e-14 ***
Service              2 23.1706 11.5853 161.5599 < 2.2e-16 ***
Destination:Service  8  4.1888  0.5236   7.3018 2.360e-05 ***
Residuals           30  2.1513  0.0717