
data(wffc)
Competitors were ranked according to their placings at each sector-session combination, and then these placings were summed. Those with the minimum total placings were the winners, thus it was not necessarily those who had the maximum points who won. For example, in Session 1 at the Waihou River, each of the 19 competitors was ranked 1 (best) to 19 (worst) according to the point system. This is the ``placing'' for that session. These placings were added up over the 5 sessions to give the ``total placings''.
All sectors have naturally wild Rainbow trout (Oncorhynchus mykiss) while Lake Otamangakau and the Whanganui River also holds Brown trout (Salmo trutta). Only these two species were targetted. The species was not recorded electronically, however a post-analysis of the paper score sheets from the two lakes showed that, approximately, less than 5 percent were Brown trout. It may be safely assumed that all the Waihou and Waimakariri fish were Rainbow trout. The gender of the fish were also not recorded electronically, and anyway, distinguishing between male and female was very difficult for small fish.
Although species and gender data were supposed to have been collected at the time of capture the quality of these variables is rather poor and furthermore they were not recorded electronically.
Note that some fish may have been caught more than once, hence these data do not represent individual fish but rather recorded captures.
Note also that a few internal discrepancies may be found within and between
the data frames
wffc
,
wffc.nc
,
wffc.indiv
,
wffc.teams
.
This is due to various reasons, such as
competitors being replaced by reserves when sick,
fish that were included or excluded upon the local judge's decision,
competitors who fished two hours instead of three by mistake, etc.
The data has already been cleaned of errors and internal inconsistencies
but a few may remain.
Yee, T. W. (2010b) On strategies and issues raised by an analysis of the 2008 World Fly Fishing Championships data. In preparation.
wffc.indiv
,
wffc.teams
,
wffc.nc
,
wffc.P1
.summary(wffc)
with(wffc, table(water, session))
# Obtain some simple plots
waihou = subset(wffc, water == "Waihou")
waimak = subset(wffc, water == "Waimakariri")
whang = subset(wffc, water == "Whanganui")
otam = subset(wffc, water == "Otamangakau")
roto = subset(wffc, water == "Rotoaira")
minlength = min(wffc[,"length"])
maxlength = max(wffc[,"length"])
nwater = c("Waihou"=nrow(waihou), "Waimakariri"=nrow(waimak),
"Whanganui"=nrow(whang), "Otamangakau"=nrow(otam),
"Rotoaira"=nrow(roto))
par(mfrow=c(2,3), las=1)
# Overall distribution of length
with(wffc, boxplot(length/10 ~ water, ylim=c(minlength, maxlength)/10,
border="blue", main="Length (cm)", cex.axis=0.5))
# Overall distribution of LOG length
with(wffc, boxplot(length/10 ~ water, ylim=c(minlength, maxlength)/10,
border="blue", log="y", cex.axis=0.5,
main="Length (cm) on a log scale"))
# Overall distribution of number of captures
pie(nwater, border="blue", main="Proportion of captures",
labels=names(nwater), density=10, col=1:length(nwater),
angle=85+30* 1:length(nwater))
# Overall distribution of number of captures
with(wffc, barplot(nwater, main="Number of captures", cex.names=0.5,
col="lightblue"))
# Overall distribution of proportion of number of captures
with(wffc, barplot(nwater / sum(nwater), cex.names=0.5, col="lightblue",
main="Proportion of captures"))
# An interesting lake
with(roto, hist(length/10, xlab="Fish length (cm)", col="lightblue",
breaks=seq(18, 70, by=3), prob=TRUE, ylim=c(0, 0.08),
border="blue", ylab="", main="Lake Rotoaira", lwd=2))
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