The Fish Catch data set contains measurements on 159 fish caught in the lake Laengelmavesi, Finland.
A data frame with 159 observations on the following 7 variables.
Weight of the fish (in grams)
Length from the nose to the beginning of the tail (in cm)
Length from the nose to the notch of the tail (in cm)
Length from the nose to the end of the tail (in cm)
Maximal height as % of Length3
Maximal width as % of Length3
The Fish Catch data set contains measurements on 159 fish caught in the lake Laengelmavesi, Finland. For the 159 fishes of 7 species the weight, length, height, and width were measured. Three different length measurements are recorded: from the nose of the fish to the beginning of its tail, from the nose to the notch of its tail and from the nose to the end of its tail. The height and width are calculated as percentages of the third length variable. This results in 6 observed variables, Weight, Length1, Length2, Length3, Height, Width. Observation 14 has a missing value in variable Weight, therefore this observation is usually excluded from the analysis. The last variable, Species, represents the grouping structure: the 7 species are 1=Bream, 2=Whitewish, 3=Roach, 4=Parkki, 5=Smelt, 6=Pike, 7=Perch. This data set was also analyzed in the context of robust Linear Discriminant Analysis by Todorov (2007), Todorov and Pires (2007).
Journal of Statistical Education, Fish Catch Data Set, [http://www.amstat.org/publications/jse/datasets/fishcatch.txt] accessed August, 2006.
Todorov, V. (2007 Robust selection of variables in linear discriminant analysis, Statistical Methods and Applications, 15, 395–407, doi:10.1007/s10260-006-0032-6.
Todorov, V. and Pires, A.M. (2007) Comparative performance of several robust linear discriminant analysis methods, REVSTAT Statistical Journal, 5, 63–83.
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data(fish) # remove observation #14 containing missing value fish <- fish[-14,] # The height and width are calculated as percentages # of the third length variable fish[,5] <- fish[,5]*fish[,4]/100 fish[,6] <- fish[,6]*fish[,4]/100 # plot a matrix of scatterplots pairs(fish[1:6], main="Fish Catch Data", pch=21, bg=c("red", "green3", "blue", "yellow", "magenta", "violet", "turquoise")[unclass(fish$Species)])