Hobson GLM - Exercise 6.6
To work out exercise 6.6 from Hobson’s book '' The weights (in grams) ofmac hine components ofa standard size made by four different workers on two different days are shown in Table; five components were chosen randomly from the output of each worker on each day. Perform an analysis of variance to test for differences among workers, among days, and possible interaction effects. What are your conclusions?
> folder <- "C:/Cauldron/garage/R/soulcraft/Volatility/Learn/Dobson-GLM/" > file.input <- paste(folder, "Table 6.19 Machine components.csv", + sep = "") > data <- read.csv(file.input, header = T, stringsAsFactors = F) > data$day <- factor(data$day) > data$worker <- factor(data$worker) |
> summary(aov(data$weight ~ data$day + data$worker + data$day:data$worker)) Df Sum Sq Mean Sq F value Pr(>F) data$day 1 6.084 6.084 4.8435 0.03508 * data$worker 3 54.622 18.207 14.4948 3.895e-06 *** data$day:data$worker 3 2.958 0.986 0.7850 0.51117 Residuals 32 40.196 1.256 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 |
Between workers, the effect is significant
- No effect due to interaction