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Profile plots is a technique of representing the multivariate data graphically. Each of the observation is represented by a diagram comprising of a sequence of equispaced vertical spikes, with each spike representing one of variables. The length of the given spike is proportional to the magnitude of the variable it represents relative to the maximum magnitude of the variable across all observations available. As an instance, consider the data below depicting the level of air pollution in four cities in the United States along with a number of other climatic and human ecologic variables. The profile plots representing these kind of data are shown in the Figure (a).
Chicago is identified as being very different from other three cities. Another instance of the profile plot is shown in the Figure (b); here the weight profiles over the time for rats in three groups are all given on the same diagram.
SO2 = Sulphur dioxide content of air (microgram per cubic metre)
Temp = Average annual temperature (F)
Manuf = Number of manufacturing enterprises employing 20 or more workers
Pop = Population size
Wind = The average annual wind speed (miles per hour)
Precip = Average annual precipitation (miles per hour)
Days = Average number of days with precipitation per year
VIF is the abbreviation of variance inflation factor which is a measure of the amount of multicollinearity that exists in a set of multiple regression variables. *The VIF value
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