Introduction to Statistics (MAT/SST 115.03 2008S)

R notes for Activity 10-5: Digital Cameras

As always, we start by reading in some values.

DC = read.csv("/home/rebelsky/Stats115/Data/DigitalCameras.csv")

As that summary suggests, the five columns in the table are Brand, Model, Type, Price, Score. Now, the book asks us to separate them by type. Lets check what kinds of types there are.


Well, it looks the the four types are advanced compact, compact, subcompact, and super-zoom. Each is probably represented as a string.

a. Segmenting and Summarizing

This problem asks us to summarize the data by type of camera. In order to get summaries, we need to break apart the data according to type. Let's start by creating a vector of prices for each of the four kinds of camera. Note that the price is is column 4, so we can use a selector to get the appropriate rows and then just take column 4. From that vector, we compute the six-number summary.

summary(DC[DC$Type=="advanced compact", 4])
summary(DC[DC$Type=="compact", 4])
summary(DC[DC$Type=="subcompact", 4])
summary(DC[DC$Type=="super-zoom", 4])

In addition to those summaries, we might make boxplots. If we're going to do aligned boxplots, we need a way to join those boxplots together. Alternately we can look for a command to draw multiple boxpots, stacked on top of each other. Fortunately, the split operation comes into play here.

boxplot(split(DC$Price,DC$Type), horizontal=T)

Exercise d: Comparing Ratings

You may recall that we recently split prices by type. Here, we want to split the Score column. The particulars of that command are left as an exercise for the reader.

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Samuel A. Rebelsky,

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