vignettes/Inference_by_eye.R

In brouwern/wildlifeR: Wildlife biology and animal ecology datasets with example analyses.

## ----setup, include=FALSE------------------------------------------------
knitr::opts_chunk$set(echo = TRUE, warnings = FALSE, message = FALSE,fig.height = 3, fig.width = 5)

## ----eval = FALSE--------------------------------------------------------
#  library(MASS)
#  data(cats)

## ----eval = FALSE--------------------------------------------------------
#  dim(cats)
#  summary(cats)

## ----eval = FALSE--------------------------------------------------------
#  library(doBy)
#  
#  #get the mean and SD
#  cat.df1 <- summaryBy(Bwt ~ Sex, data = cats, FUN = c(mean,sd))
#  
#  #get the sample size using length()
#  cat.df2 <- summaryBy(Bwt ~ Sex, data = cats, FUN = c(length))
#  
#  #make a combined dataframe
#  cat.df3 <- merge(cat.df1,cat.df2)
#  
#  #calculate the standard error SE by hand
#  
#  cat.df3$SE <- cat.df3$Bwt.sd/sqrt(cat.df3$Bwt.length)
#  

## ----eval = FALSE--------------------------------------------------------
#  
#  cat.df3
#  

## ----eval = FALSE--------------------------------------------------------
#  par(mfrow = c(1,1),mar = c(3,3.5,1,1))
#  
#  boxplot(Bwt ~ Sex, data = cats)

## ----eval = FALSE--------------------------------------------------------
#  library(Hmisc)
#  par(mfrow = c(1,2),mar = c(3,3.5,1,1))
#  
#  y.lim <- c(2.295,3)
#  errbar(1:2,
#         y = cat.df3$Bwt.mean,
#         yplus =cat.df3$Bwt.mean + cat.df3$SE,
#         yminus = cat.df3$Bwt.mean-cat.df3$SE,
#         xlab = "",
#         ylab = "",
#         xlim=c(0.5,2.5),
#         ylim = y.lim,
#         xaxt="n",cex =1)
#  axis(side=1,at=1:2,labels=cat.df3$Sex)
#  mtext("Sex", side = 1, line = 2, cex = 2)
#  mtext("Mass (g)", side = 2, line = 2.1, cex = 1.3)
#  
#  errbar(1:2,
#         y = cat.df3$Bwt.mean,
#         yplus =cat.df3$Bwt.mean + 1.96*cat.df3$SE,
#         yminus = cat.df3$Bwt.mean-1.96*cat.df3$SE,
#         xlab = "",
#         ylab = "",
#         xlim=c(0.5,2.5),
#         ylim = y.lim,
#         xaxt="n",cex =1)
#  axis(side=1,at=1:2,labels=cat.df3$Sex)
#  mtext("Sex", side = 1, line = 2, cex = 2)
#  mtext("Mass (g)", side = 2, line = 2.1, cex = 1.3)
#  
#  

## ----eval = FALSE--------------------------------------------------------
#  cat.df3.mod <- cat.df3
#  cat.df3.mod$Bwt.mean[1] <- cat.df3$Bwt.mean[2]-cat.df3$Bwt.mean[2]*0.0425

## ----eval = FALSE--------------------------------------------------------
#  y.lim <- c(2.6975,3)
#  par(mar = c(3,3.5,1,1))
#  errbar(1:2,
#         y = cat.df3.mod$Bwt.mean,
#         yplus =cat.df3.mod$Bwt.mean + cat.df3.mod$SE,
#         yminus = cat.df3.mod$Bwt.mean-cat.df3.mod$SE,
#         xlab = "",
#         ylab = "",
#         xlim=c(0.5,2.5),
#         ylim = y.lim,
#         xaxt="n",cex =1)
#  axis(side=1,at=1:2,labels=cat.df3.mod$Sex)
#  mtext("Sex", side = 1, line = 2, cex = 2)
#  mtext("Mass (g)", side = 2, line = 2.1, cex = 1.3)
#  
#  errbar(1:2,
#         y = cat.df3.mod$Bwt.mean,
#         yplus =cat.df3.mod$Bwt.mean + 1.96*cat.df3.mod$SE,
#         yminus = cat.df3.mod$Bwt.mean-1.96*cat.df3.mod$SE,
#         xlab = "",
#         ylab = "",
#         xlim=c(0.5,2.5),
#         ylim = y.lim,
#         xaxt="n",cex =1)
#  axis(side=1,at=1:2,labels=cat.df3.mod$Sex)
#  mtext("Sex", side = 1, line = 2, cex = 2)
#  mtext("Mass (g)", side = 2, line = 2.1, cex = 1.3)
#  
#  
#  

## ----eval = FALSE--------------------------------------------------------
#  
#  t.test(Bwt ~ Sex, data = cats)
#  
#  

## ----eval = FALSE--------------------------------------------------------
#  
#  summary(lm(Bwt ~ -1+Sex, data = cats))
#