pdf("mathlsd.pdf")

# Read in data from ASCII formatted (Fixed Width File)

mathlsddat <- read.fwf("C:\\data\\mathlsd.dat", width=c(4,8), 
 col.names=c("lsd","math"))


# Create a dataset (frame) from input data

mathlsd <- data.frame(mathlsddat)

# Attach the dataset for analysis 

attach(mathlsd)

mathlsd

# Fit the simple linear regression model with dependent variable = math (score)
#  and independent variable = lsd (concentration)

mathlsd.reg <- lm(math ~ lsd)

# Plot the data and regression line (Note you enter X first, then Y in plot statement)

plot(lsd,math)
abline(mathlsd.reg)

# Print out the estimates, standard errors and t-tests, R-Square, and F-test

summary(mathlsd.reg)

# Print out the ANOVA table (Sums of Squares and degrees of freedom)

anova(mathlsd.reg)

# Compute the correlation coefficient

cor(math,lsd)

# Test whether the population correlation coefficient is 0 (Identical to t-test for slope of regression line)

cor.test(math,lsd)

dev.off()