统计学(第8版)P209习题10.3

data <-data.frame(
  method = c(rep("A",9),rep("B",9),rep("c",8)),
  time = c(8.8,9.3,8.7,9.0,8.6,8.3,9.5,9.4,9.2,
           8.2,6.7,7.4,8.0,8.2,7.8,8.8,8.4,7.9,
           8.6,8.5,9.1,8.2,8.3,7.9,9.9,9.4)
  )

data %>% 
  aov(time ~ method, .) %>% 
  summary()
            Df Sum Sq Mean Sq F value  Pr(>F)   
method       2  5.349  2.6746   8.275 0.00196 **
Residuals   23  7.434  0.3232                   
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
data %>% 
  ggplot(aes(reorder(method, time), 
             time, col = method)) +
  geom_boxplot()

统计学(第8版)P209习题10.6

data <- data.frame(
  area = rep(c("A1","A2","A3"),3),
  method = c(rep("B1",3),rep("B2",3),rep("B3",3)),
  sales = c(45,50,35,75,50,65,30,40,50)
)

data %>% 
  aov(sales ~ area + method,.) %>% 
  summary()
            Df Sum Sq Mean Sq F value Pr(>F)
area         2   22.2    11.1   0.073  0.931
method       2  955.6   477.8   3.127  0.152
Residuals    4  611.1   152.8

统计学(第8版)P209习题10.7

data <- data.frame(
  location = rep(c(rep("小区",3),rep("写字楼",3),rep("郊区",3)),4),
  competitors = c(rep("0个",9),rep("1个",9), rep("2个",9), rep("3个以上",9)),
  sales = c(41,30,45,25,31,22,18,29,33,
            38,31,39,29,35,30,22,17,25,
            59,48,51,44,48,50,29,28,26,
            47,40,39,43,42,53,24,27,32)
)


data %>% 
  aov(sales ~ location + competitors + location:competitors,.) %>% 
  summary()
                     Df Sum Sq Mean Sq F value   Pr(>F)    
location              2 1736.2   868.1  34.305 9.18e-08 ***
competitors           3 1078.3   359.4  14.204 1.57e-05 ***
location:competitors  6  503.3    83.9   3.315   0.0161 *  
Residuals            24  607.3    25.3                     
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
data %>% 
  aov(sales ~ location*competitors,.) %>% 
  summary()
                     Df Sum Sq Mean Sq F value   Pr(>F)    
location              2 1736.2   868.1  34.305 9.18e-08 ***
competitors           3 1078.3   359.4  14.204 1.57e-05 ***
location:competitors  6  503.3    83.9   3.315   0.0161 *  
Residuals            24  607.3    25.3                     
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1