Graphical Methods for Data Analysis

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Transcript Graphical Methods for Data Analysis

Star/Radar/Spider Plot
Figure 1 :A typical radar graph with two plots
Purpose

The star plot is a method of displaying multivariate
data.

Each star represents a single observation.

Typically, star plots are generated in a multi-plot
format with many stars on each page and each star
representing one observation .

Star plots are used to examine the relative values for
a single data point (e.g., point 3 is large for
variables 2 and 4, small for variables 1, 3, 5, and 6)
and to locate similar points or dissimilar points
Sample Plot
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
The plot below contains the star plots of 16 cars.
The variable list for the sample star plot is:
1. Price
2. Mileage (MPG)
3. 1978 Repair Record (1 = Worst, 5 = Best)
4. 1977 Repair Record (1 = Worst, 5 = Best)
5. Headroom
6. Rear Seat Room
7. Trunk Space
8. Weight
9. Length
We can look at these plots individually or we can use them to
identify clusters of cars with similar features.
We can look at the star plot of the Cadillac Seville :
it is one of the most expensive cars,
gets below average (but not among the worst) gas mileage,
has an average repair record,
and has average-to-above-average roominess and size.
 We can then compare the Cadillac models (the last three
plots) with the AMC models (the first three plots).
The AMC models tend to be inexpensive,
have below average gas mileage,
and are small in both height and weight and in roominess.
The Cadillac models are expensive,
have poor gas mileage,
and are large in both size and roominess .

Questions
The star plot can be used to answer the following
questions:

What variables are dominant for a given
observation?

Which observations are most similar, i.e., are there
clusters of observations?

Are there outliers?
Weakness in Technique
Star plots are helpful for small-to-moderate-sized
multivariate data sets.
Their primary weakness is that their effectiveness is
limited to data sets with less than a few hundred
points.
After that, they tend to be overwhelming .