1. In previous assignments, you looked at various aspects of a data on two species of...

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1. In previous assignments, you looked at various aspects of a data on two species of rock crabs; in this problem, you will use linear discriminant analysis to derive a rule for classifying the colour and sex of a crab. The data are in the file crabs, txt on Quercus. The data can be read into R using the following code: > x colour sex < x[[2]] > FL < x[[4]] > RW CL < x[[6]] > CW BD group group [sex=="M"&colour=="B"] group [sex=="F"&colour=="B"] group [sex=="M"&colour=="0"] < 3 > group [sex=="F"&colour=="0"] group library (MASS) # library with lda. > r $class 2 1 1 2 1 1 2 1 1 1 1 1 1 1 [1] 1 2 1 11 11 1 1 1 1 1 1 1 1 1 [45] 1 1 1 1 1 1 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 [89] 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 333 [133] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 3 4 4 4 4 4 4 4 4 4 4 4 4 444 [177] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4444 Levels: 1 2 3 4 $terms group FL + RW + CL + CW + BD attr(, "variables") list(group, FL, RW, CL, CW, BD) attr(,"factors") FL RW CL CW BD group 0 0 0 0 0 FL RW CL CW BD 1 0000 0 1 0 0 0 0 0 100 00010 0 0 0 0 1 attr(,"term.labels") [1] "FL" "RW" "CL" "CW" "BD" attr(, "order") [1] 1 1 1 1 1 attr(, "intercept") [1] 1 attr(,"response") [1] 1 attr(,".Environment") attr(, "predvars") list(group, FL, RW, CL, CW, BD) attr(, "dataClasses") group FL RW CL CW BD "factor" "numeric" "numeric" "numeric" "numeric" "numeric" $call lda(formula group FL + RW + CL + CW + BD, CV = T) $xlevels named list() 1. In previous assignments, you looked at various aspects of a data on two species of rock crabs; in this problem, you will use linear discriminant analysis to derive a rule for classifying the colour and sex of a crab. The data are in the file crabs, txt on Quercus. The data can be read into R using the following code: > x colour sex < x[[2]] > FL < x[[4]] > RW CL < x[[6]] > CW BD group group [sex=="M"&colour=="B"] group [sex=="F"&colour=="B"] group [sex=="M"&colour=="0"] < 3 > group [sex=="F"&colour=="0"] group library (MASS) # library with lda. > r $class 2 1 1 2 1 1 2 1 1 1 1 1 1 1 [1] 1 2 1 11 11 1 1 1 1 1 1 1 1 1 [45] 1 1 1 1 1 1 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 [89] 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 333 [133] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 3 4 4 4 4 4 4 4 4 4 4 4 4 444 [177] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4444 Levels: 1 2 3 4 $terms group FL + RW + CL + CW + BD attr(, "variables") list(group, FL, RW, CL, CW, BD) attr(,"factors") FL RW CL CW BD group 0 0 0 0 0 FL RW CL CW BD 1 0000 0 1 0 0 0 0 0 100 00010 0 0 0 0 1 attr(,"term.labels") [1] "FL" "RW" "CL" "CW" "BD" attr(, "order") [1] 1 1 1 1 1 attr(, "intercept") [1] 1 attr(,"response") [1] 1 attr(,".Environment") attr(, "predvars") list(group, FL, RW, CL, CW, BD) attr(, "dataClasses") group FL RW CL CW BD "factor" "numeric" "numeric" "numeric" "numeric" "numeric" $call lda(formula group FL + RW + CL + CW + BD, CV = T) $xlevels named list()