Boomerang

library(s20x)
b.df = read.table('boomerang.txt', header = TRUE)
b.df$type = factor(b.df$type)
boxplot(distances ~ type, data = b.df)

b.fit = lm(distances ~ type, data = b.df)
normcheck(b.fit)

onewayPlot(distances ~ type, data = b.df)

summaryStats(distances ~ type, data = b.df)

eovcheck(distances ~ type, data = b.df)

trans.b = log(b.df$distances)
normcheck(trans.b)

t.fit=lm(log(distances) ~ type, data = b.df)
eovcheck(t.fit)

t.test(log(distances) ~ type, var.equal = FALSE, data = b.df)

    Welch Two Sample t-test

data:  log(distances) by type
t = 2.1261, df = 20.594, p-value = 0.04576
alternative hypothesis: true difference in means between group Original and group Prototype is not equal to 0
95 percent confidence interval:
 0.0125843 1.2043418
sample estimates:
 mean in group Original mean in group Prototype 
             -0.3031708              -0.9116339 

ci = t.test(log(distances) ~ type, var.equal = FALSE, data = b.df)$conf.int
exp(ci)

[1] 1.012664 3.334564
attr(,"conf.level")
[1] 0.95