# R Dataset / Package DAAG / possum

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dataset-24907.csv | 6.25 KB |

Documentation |
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On this Picostat.com statistics page, you will find information about the possum data set which pertains to Possum Measurements. The possum data set is found in the DAAG R package. You can load the possum data set in R by issuing the following command at the console data("possum"). This will load the data into a variable called possum. If R says the possum data set is not found, you can try installing the package by issuing this command install.packages("DAAG") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the possum R data set. The size of this file is about 6,399 bytes. ## Possum Measurements## DescriptionThe ## Usagepossum ## FormatThis data frame contains the following columns: - case
observation number - site
one of seven locations where possums were trapped - Pop
a factor which classifies the sites as `Vic` Victoria,`other` New South Wales or Queensland- sex
a factor with levels `f` female,`m` male- age
age - hdlngth
head length - skullw
skull width - totlngth
total length - taill
tail length - footlgth
foot length - earconch
ear conch length - eye
distance from medial canthus to lateral canthus of right eye - chest
chest girth (in cm) - belly
belly girth (in cm)
## SourceLindenmayer, D. B., Viggers, K. L., Cunningham, R. B., and Donnelly, C. F. 1995. Morphological variation among columns of the mountain brushtail possum, Trichosurus caninus Ogilby (Phalangeridae: Marsupiala). Australian Journal of Zoology 43: 449-458. ## Examplesboxplot(earconch~sex, data=possum) pause()sex <- as.integer(possum$sex) oldpar <- par(oma=c(2,4,5,4)) pairs(possum[, c(9:11)], pch=c(0,2:7), col=c("red","blue"), labels=c("tail\nlength","foot\nlength","ear conch\nlength")) chh <- par()$cxy[2]; xleg <- 0.05; yleg <- 1.04 oldpar <- par(xpd=TRUE) legend(xleg, yleg, c("Cambarville", "Bellbird", "Whian Whian ", "Byrangery", "Conondale ","Allyn River", "Bulburin"), pch=c(0,2:7), x.intersp=1, y.intersp=0.75, cex=0.8, xjust=0, bty="n", ncol=4) text(x=0.2, y=yleg - 2.25*chh, "female", col="red", cex=0.8, bty="n") text(x=0.75, y=yleg - 2.25*chh, "male", col="blue", cex=0.8, bty="n") par(oldpar) pause()sapply(possum[,6:14], function(x)max(x,na.rm=TRUE)/min(x,na.rm=TRUE)) pause()here <- na.omit(possum$footlgth) possum.prc <- princomp(possum[here, 6:14]) pause()plot(possum.prc$scores[,1] ~ possum.prc$scores[,2], col=c("red","blue")[as.numeric(possum$sex[here])], pch=c(0,2:7)[possum$site[here]], xlab = "PC1", ylab = "PC2") # NB: We have abbreviated the axis titles chh <- par()$cxy[2]; xleg <- -15; yleg <- 20.5 oldpar <- par(xpd=TRUE) legend(xleg, yleg, c("Cambarville", "Bellbird", "Whian Whian ", "Byrangery", "Conondale ","Allyn River", "Bulburin"), pch=c(0,2:7), x.intersp=1, y.intersp=0.75, cex=0.8, xjust=0, bty="n", ncol=4) text(x=-9, y=yleg - 2.25*chh, "female", col="red", cex=0.8, bty="n") summary(possum.prc, loadings=TRUE, digits=2) par(oldpar) pause()require(MASS) here <- !is.na(possum$footlgth) possum.lda <- lda(site ~ hdlngth+skullw+totlngth+ taill+footlgth+ earconch+eye+chest+belly, data=possum, subset=here) options(digits=4) possum.lda$svd # Examine the singular values plot(possum.lda, dimen=3) # Scatterplot matrix - scores on 1st 3 canonical variates (Figure 11.4) possum.lda -- Dataset imported from https://www.r-project.org. |

R Output | Date |
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Picostat Output - Simple Linear Regression | Apr 9, 2020 |

Picostat Output - Simple Linear Regression | Apr 9, 2020 |

Picostat Output - Simple Linear Regression | Apr 9, 2020 |

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