## ------------------------------------------------------------------------
BirdData <- data.frame(
            Tarsus  = c(22.3, 19.7, 20.8, 20.3, 20.8, 21.5, 20.6, 21.5),
            Head    = c(31.2, 30.4, 30.6, 30.3, 30.3, 30.8, 32.5, 31.6),
            Weight  = c(9.5, 13.8, 14.8, 15.2, 15.5, 15.6, 15.6, 15.7),
            Wingcrd = c(59, 55, 53.5, 55, 52.5, 57.5, 53, 55),
            Species = c('A', 'A', 'A', 'A', 'A',  'B', 'B', 'B')
            )

## ------------------------------------------------------------------------
t.test(BirdData$Tarsus, mu = 20)

## ------------------------------------------------------------------------
t.test(x = BirdData$Tarsus[BirdData$Species == 'A'], 
       y = BirdData$Tarsus[BirdData$Species == 'B'])

## ------------------------------------------------------------------------
t.test(x = BirdData$Tarsus[BirdData$Species == 'A'], 
       y = BirdData$Tarsus[BirdData$Species == 'B'],
       var.equal = TRUE)

## ------------------------------------------------------------------------
before <- c(20, 15, 10, 5, 20, 15, 10, 5, 20, 15, 10, 5, 20, 15, 10, 5)
after <- c(23, 16, 10, 4, 22, 15, 12, 7, 21, 16, 11, 5, 22, 14, 10, 6)

t.test(before, after)
t.test(before, after, paired = TRUE)

## ------------------------------------------------------------------------
t.test(x = before - after, mu = 0, var.equal = TRUE)

## ------------------------------------------------------------------------
wilcox.test(x = BirdData$Tarsus[BirdData$Species == 'A'], 
            y = BirdData$Tarsus[BirdData$Species == 'B'])

## ------------------------------------------------------------------------
#dat <- read.table(file = "http://www.simonqueenborough.info/R/data/sparrows.txt", header = TRUE)
dat <- read.table('~/Dropbox/MyLab/website/R/data/sparrows.txt', header = TRUE, sep = '\t')

## ------------------------------------------------------------------------
dat$fObserver <- as.factor(dat$Observer)

## ---- fig.cap = "Differences in Tarsus length measured by different Observers"----
par(mfrow = c(1, 2), lwd = 2, las = 1)

# 1. First a boxplot
boxplot(dat$Tarsus ~ dat$fObserver,
       xlab = 'Observer')

# 2. Then, a barplot:
## use tapply() to get means and sd
MeanTarsus <- tapply(dat$Tarsus, dat$fObserver, mean)
SDTarsus   <- tapply(dat$Tarsus, dat$fObserver, sd)

## calculate mid-points of bars, to plot error bars
MidPoints <- barplot(MeanTarsus, plot = FALSE)

barplot(MeanTarsus, ylim = c(0, 30),
       xlab = 'Observer')
segments(x0 = MidPoints, x1 = MidPoints,
         y0 = MeanTarsus + SDTarsus, y1 = MeanTarsus - SDTarsus)

## ------------------------------------------------------------------------
m_obs <- aov(Tarsus ~ fObserver, data = dat)
summary(m_obs)

## ------------------------------------------------------------------------
kruskal.test(Tarsus ~ fObserver, data = dat)

## ------------------------------------------------------------------------
m_additive <- aov(Tarsus ~ Species + Sex, data = dat)
summary(m_additive)

## ------------------------------------------------------------------------
m_interaction <- aov(Tarsus ~ Species * Sex, data = dat)
summary(m_interaction)

## ------------------------------------------------------------------------
posthoc <- TukeyHSD(m_obs)
posthoc

## ------------------------------------------------------------------------
posthoc <- TukeyHSD(m_additive)
posthoc