# Playing with the dice data from class

# This is how we did it in class.  We were jumping around a little in
# the order we executed stuff, so make sure the names of the columns
# of the data frames you're using are the correct ones.

# The data:

group1a <- c(0,2,1,1,3,1,1,0,1,0,0,2,2,1,1,1,1,1,1,1,2,1,0,1,1,2,2,1,1,0,0,2,2,2,2,2,1,0,1,1,0,0,0,3,0,1,3,1,2,0,0,0,1,0,1,1,2,0,1,1,0,2,1,1,1,1,2,1,3,0,0,1,2,0,3,1,1,1,1,1,1,0,0,2,1,1,1,2,1,2,1,0,0,0,0,1,2,0,3,2)

group1b <- read.csv("http://cs.marlboro.edu/courses/spring2013/statistics/wiki/wiki.attachments/Dice_Rolls.csv")

group1b <- as.vector(group1a$X0)

group1 <- c(group1a, group1b)


group2a <- read.csv("http://cs.marlboro.edu/courses/spring2013/statistics/wiki/wiki.attachments/Jar_3.csv")

group2a <- as.vector(group2a$X0)

group2b <- read.csv("http://cs.marlboro.edu/courses/spring2013/statistics/wiki/wiki.attachments/DieData.csv")

group2b <- as.vector(group2b$X1)


group2c <- read.csv("http://cs.marlboro.edu/courses/spring2013/statistics/wiki/wiki.attachments/sherpa.csv")

group2c <- as.vector(group2c$X2)

group2 <- c(group2a, group2b, group2c)


group3 <- read.csv("http://cs.marlboro.edu/courses/spring2013/statistics/wiki/wiki.attachments/Number_of_sixes.csv")

group3 <- as.vector(group3$Number.of.6s)

# Point estimates for the means:

mean(group1)
mean(group2)
mean(group3)


# The margin of error (normal distribution, 99% confidence):

qnorm(0.995) * sd(group1) / sqrt(length(group1))
qnorm(0.995) * sd(group2) / sqrt(length(group2))
qnorm(0.995) * sd(group3) / sqrt(length(group3))