Summary

Parental attendance and feeding data in a .csv file

YEAR,JUDA,CHICK,FISH,TIME
2012,171,B,0,3600
2012,171,C,1,127
...
2013,168,G,0,0
...
2016,184,S,0,3600

load .csv into R
gu <- read.csv("GU1216.csv")
gu$JUDA <- factor(gu$JUDA)
gu$CHICK <- factor(gu$CHICK)
gu$YEAR <- factor(gu$YEAR)
attach(gu)

plot parental attendance against year, Julian date, and focal site
plot(YEAR,TIME)
Parental attendence vs Year
plot(JUDA,TIME)
Parental attendence vs Julian date
plot(CHICK,TIME)
Parental attendence vs Chick
plot(ecdf(TIME), do.points=FALSE, verticals=TRUE)
Parental attendence
gu12 <- read.csv("GU2012.csv")
gu13 <- read.csv("GU2013.csv")
gu14 <- read.csv("GU2014.csv")
gu15 <- read.csv("GU2015.csv")
gu16 <- read.csv("GU2016.csv")

plot(ecdf(gu12$TIME), do.points=FALSE, verticals=TRUE, add=TRUE)
plot(ecdf(gu14$TIME), do.points=FALSE, verticals=TRUE, add=TRUE)

Parental attendence
> ks.test(g12$TIME,gu13$TIME)

	Two-sample Kolmogorov-Smirnov test

data:  gu12$TIME and gu13$TIME
D = 0.16447, p-value = 0.1018
alternative hypothesis: two-sided

Warning message:
In ks.test(gu12$TIME, gu13$TIME) :
  p-value will be approximate in the presence of ties


> ks.test(g12$TIME,gu14$TIME)

D = 0.25975, p-value = 0.001482


> ks.test(g12$TIME,gu15$TIME)

D = 0.15758, p-value = 0.1503


> ks.test(g12$TIME,gu16$TIME)

D = 0.11397, p-value = 0.5193


> ks.test(g13$TIME,gu14$TIME)

D = 0.14989, p-value = 0.1353


> ks.test(g13$TIME,gu15$TIME)

D = 0.096481, p-value = 0.6497


> ks.test(g13$TIME,gu16$TIME)

D = 0.12279, p-value = 0.3549


> ks.test(g14$TIME,gu15$TIME)

D = 0.19373, p-value = 0.02887


> ks.test(g14$TIME,gu16$TIME)

D = 0.20478, p-value = 0.01921


> ks.test(g15$TIME,gu16$TIME)

D = 0.10995, p-value = 0.5315




References