# Make a boxplot of the data from chickwts
plot(weight~feed,data = chickwts)
# Create anova object
weights.aov <- aov(weight ~ feed, data =chickwts)
# Display the ANOVA table
summary(weights.aov)
# Display the grand mean and all group means, 
# plus group sizes
model.tables(weights.aov,"means")
# Perform Tukey's Honest Significant Difference Test
# as post-hoc analysis
posthoc <- TukeyHSD(weights.aov)
# Result of analysis gives difference of means, and upper and lower
# values of confidence interval, and adjusted p-value for that
# pair of groups. 
posthoc
# Plots the confidence intervals
plot(posthoc)
# Change the y axis to be perpendicular to the axis
plot(posthoc,las = 1)
# ------------
# Chi-Squared Goodness-of-Fit Test
# observed values from sample
observed = c(11,10)
# expected probabilities
probs = c(0.68,0.32)
# perform the chi-square test
chisq.test(observed,p = probs)
# Make a table of only sex and eye color
x = xtabs(Freq ~ Sex + Eye, data = HairEyeColor)
# Perform a Chi-Squared Test comparing eye color
# distribution in males and females
chisq.test(x)
# Make a table of only hair and eye color
x = xtabs(Freq ~ Hair + Eye, data = HairEyeColor)
# Display the table
x
# Perform the chi-squared test
chisq.test(x)