Introduction to Statistics (MAT/SST 115.03 2008S)
You can use the following command to make the vector of deal amounts.
DealAmounts = c(0.01, 1, 5, 10, 25, 50, 75, 100, 200, 300, 400, 500, 750, 1000, 5000, 10000, 25000, 50000, 75000, 100000, 200000, 300000, 400000, 500000, 750000, 1000000)
You can use
mean to compute the
mean of a vector and
median to compute
the median of a vector.
Although the book says that the data are stored in the file
Matching, we've separated the data into
three separate files:
All are stored in the standard data directory for this course.
Recall that you can read a file into a frame with a command like
MonopolyPrices = read.csv("/home/rebelsky/Stats115/Data/MonopolyPrices.csv")
You should be able to figure out the commands to read the other two data sets.
We need to load an appropriate library to do dotplots, but otherwise it remains straightforward. Particularly since we do not plan to use these graphs for anything but a quick observation, we don't even need to fool with axis labels.
library(BHH2, lib="/home/rebelsky/Stats115/Packages") dotPlot(MonopolyPrices, main="Prices of Monopoly Properties")
You might note something a bit strange about this command.
Traditionally, we use
dotPlot with vectors.
And, if you think about it carefully,
a data frame, rather than a vector. So, why does the command work?
Apparantly, R is smart enough to treat a data frame with one column
as a vector, at least for this plot.
If, however, you want to create a histogram, you'll need to
extract the column (which is also called
Here's a fine-enough grained histogram that it replicates the dotplot.
As you already know, you can get the mean and median separately
You can also get them together with a host of other information
The data are now stored in
Rowers04.csv. You can read
them in as follows:
Rowers = read.csv("/home/rebelsky/Stats115/Data/Rowers04.csv")
Refer to the instructions from a previous activity to see how to make
dotplots and how to have R compute a mean and median. In each case,
you want to use the vector
This activity asks you to remove one row (corresponding to Cipollone, the coxswain) and, later, to change the weight of Schroeder. It turns out that you need different tools for the two activities. To delete rows, you use the row selection commands. For example,
Rowers = Rowers[Rowers$Name != "Cipollone",]
To change weight use the
Remember that R pauses while you're editing the data set, so you must close the editing window before doing anything else.
This activity requires a bit more work with R than we've done in previous exercises. We start by reading in values.
SeatBeltUsage = read.csv("/home/rebelsky/Stats115/Data/SeatBeltUsage05.csv")
The first step is to separate the table into two parts.
Primary = SeatBeltUsage[SeatBeltUsage$LawType == "Primary", ] Secondary = SeatBeltUsage[SeatBeltUsage$LawType == "Secondary", ]
You will need to extract the
column from each in order to compute dot plots, means, and medians.
It may be helpful to draw each dot plot in a separate window.
In R, the way we create a new output window depends on the
computer system we're using. On Linux (which we use in class),
the command is
X11(). On a Mac, the command is
quartz(). On Microsoft windows, the command is
windows(). Hence, on our Linux boxes, you might
create new windows for the two new plots with.
X11() dotPlot(Primary$CompliancePercentage) X11() dotPlot(Secondary$CompliancePercentage)
You can load the data for this activity with
MarriageAges = read.csv("/home/rebelsky/Stats115/Data/MarriageAges.csv")
Since this is a homework activity, the remaining instructions are left for you to determine.
As you may recall from Activity 8-3, you can load the data for this activity with
QuizPercentages = read.csv("/home/rebelsky/Stats115/Data/QuizPercentages.csv")
Since this is a homework activity, the remaining instructions are left
for you to determine. (Recall that you can use
fix to change the data.
Copyright (c) 2007-8 Samuel A. Rebelsky.
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