Introduction to Statistics (MAT/SST 115.03 2008S)

R notes for Activity 19-5: Sleeping Times


I will gather your sleep time data at the start of class and enter them into a file. You can read them into a table with

SleepData = read.csv("/home/rebelsky/Stats115/Data/SleepData.csv")
SleepTimes = SleepData$HoursSlept

The second line allows us to refer to the vector as SleepTimes.

19-5 a: Graphical Displays

You should refer to activity 19-3 c for ideas of graphical displays.

19-5 b: Sample Statistics

You can get sample size, sample mean, and sample standard deviation with

length(SleepTimes)
mean(SleepTimes)
sd(SleepTimes)

19.5 d: Confidence Interval

Since we have all of the original data, the easiest way to get the confidence interval is to use the t.test function. You should substitute your own guess as to the mean hours slept (in place of 6).

t.test(SleepTimes, mu=6, conf.level=.90)

Of course, you might also want to provide R with step-by-step instructions.

x_bar = mean(SleepTimes)
n = length(SleepTimes)
s = sd(SleepTimes)
t_star = qt(0.95, n-1)
ci_lower = x_bar - t_star*s/sqrt(n)
ci_upper = x_bar + t_star*s/sqrt(n)
c(ci_lower, ci_upper)

19-5 e: Counting

Rather than counting values by hand, you can get R to produce a vector of the times in this interval with

NearMedian = SleepTimes[(SleepTimes > ci_lower) & (SleepTimes < ci_upper)]
length(NearMedian)

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Samuel A. Rebelsky, rebelsky@grinnell.edu

Copyright (c) 2007-8 Samuel A. Rebelsky.

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