# BloodPressure Example
# R script for Lab 1 problems.

# Prob1
# Create bp1 and bp2 data frames.
bp1 = read.table("c:/datasets/blood-pressure1.txt", header=TRUE)
bp2 = read.table("c:/datasets/blood-pressure2.txt", header=TRUE)

# Prob2
# Print bp1 and bp2 data frames.
cat("bp1 dataframe:\n")
print(bp1)
cat("bp2 dataframe:\n")
print(bp2)

# Prob3
# Compute univariate statistics from
# standing and supine columns in bp1.
cat("Sample mean for Standing in bp1:\n")
mean(bp1$Standing)
cat("\nSample SD for Standing in bp1:\n")
sd(bp1$Standing)
cat("\nSample quantiles for Standing in bp1:\n")
quantile(bp1$Standing, c(0.01, 0.05, 0.25, 0.50, 0.75, 0.95, 0.99))
cat("\nInterquartile range for Standing in bp1:\n")
IQR(bp1$Standing)

cat("Sample mean for Supine in bp1:\n")
mean(bp1$Supine)
cat("\nSample SD for Supine in bp1:\n")
sd(bp1$Supine)
cat("\nSample quantiles for Supine in bp1:\n")
quantile(bp1$Supine, c(0.01, 0.05, 0.25, 0.50, 0.75, 0.95, 0.99))
cat("\nInterquartile range for Supine in bp1:\n")
IQR(bp1$Supine)

# Prob 4 
# Skip this problem if using R.

pdf = pdf("c:/datasets/bp.pdf")

# Prob 5
# Create histograms for Standing and Supine
hist(bp1$Standing, 
   xlab="Blood Pressure in Standing Position")
hist(bp1$Standing, breaks=seq(100, 700, 200),
   xlab="Blood Pressure in Standing Position")
hist(bp1$Standing, breaks=seq(100, 600, 50),
   xlab="Blood Pressure in Standing Position")
hist(bp1$Supine,
   xlab="Blood Pressure in Supine Position")
hist(bp1$Supine, breaks=seq(0, 200, 100),
   xlab="Blood Pressure in Supine Position")
hist(bp1$Supine, breaks=seq(0, 200, 25),
   xlab="Blood Pressure in Supine Position")

# Prob 6
# Create normal plots for Standing and Supine
qqnorm(bp1$Standing, 
   xlab="Blood Pressure in Standing Position")
qqnorm(bp1$Supine, 
   xlab="Blood Pressure in Supine Position")

# Prob 7
# Create side-by-side boxplots for Press
# using Pos as the independent variable.
boxplot(bp2$Press ~ bp2$Pos, 
   xlab="Position in which Blood Pressure is Measured",
   ylab="Blood Pressure")

dev.off( )

# Prob 8
# Obtain confidence intervals from one-sample t-test 
# output.  We are not actually performing a t-test,
# just obtaining the confidence interval from the output. 
cat("\nOne-sample t-test output:\n")
t.test(bp1$Standing, y=NULL, alternative="two.sided", 
   paired=FALSE, conf.level=0.95)
t.test(bp1$Supine, y=NULL, alternative="two.sided", 
   paired=FALSE, conf.level=0.95)

# Prob 9
# Paired-sample t-test
cat("\nPaired-sample t-test output:")
t.test(bp1$Standing, bp1$Supine, alternative="two.sided", 
   paired=TRUE, conf.level=0.95)

# Prob 10
# Independent 2-sample t-test
cat("\nIndependent 2-sample t-test output:\n")
t.test(bp1$Standing, bp1$Supine, alternative="two.sided", 
   paired=FALSE, conf.level=0.95)