#This function creates a scatter plot of weight vs. height 
#by gender.  It also gives the simple linear regression lines.
#
myplot<-function(data) {
  #Extract the data I want from "studdata"
  gender<-data[,2]
  height<-data[,6]
  weight<-data[,7]
  female<-gender=="F"

  #Calculate SLR lines
  SLR.F<-lsfit(x=height[female],y=weight[female])$coef
  SLR.M<-lsfit(x=height[!female],y=weight[!female])$coef

  #Set up an empty plot (i.e. no data)
  plot(height,weight,type="n",
       xlab="Height (in.)",ylab="Weight (ibs.)",
       main="Weight vs. Height by Gender",
       sub="Spring 2004 STAT330 Data")
  
  #Add the points to the plot
  points(height[female],weight[female],pch="F",cex=0.5)
  points(height[!female],weight[!female],pch="M",cex=0.5)

  #Add the regression lines to the plot
  abline(coef=SLR.F,lty="solid")
  abline(coef=SLR.M,lty="dotted")

  #Add a legend (for the regression lines) to the plot
  legend(x=c(60,65),y=c(270,290),legend=c("Females","Males"),
         lty=c("solid","dotted"),cex=0.75)

  #Add some text to the plot
  slr.f=paste("Wght = ",round(SLR.F[1],1)," + ",round(SLR.F[2],1),"(Hght)",
              sep="")
  slr.m=paste("Wght = ",round(SLR.M[1],1)," + ",round(SLR.M[2],1),"(Hght)",
              sep="")
  text(x=c(60,60),y=c(130,180),labels=c(slr.f,slr.m),cex=0.5)
  p<-which(data[,7]>270)
  text(x=75,y=280,labels=paste("Obs.",p),cex=0.75)
  arrows(x0=73.9,y0=280,x1=data[p,6]+.1,y1=data[p,7]-.1,length=0.1)   
}