# Groundhog Day Predictions (Shadow = 1) --- Logistic Regression

# Data Source:  www.stormfax.com/ghogday.htm

groundhog <- read.table("groundhog.dat", header=TRUE)


plot(groundhog)


groundhog.model <- glm(Shadow ~ Year, family=binomial, data=groundhog)
summary(groundhog.model)

reduced.model <- glm(Shadow ~ 1, family=binomial, data=groundhog)
anova(reduced.model, groundhog.model, test="Chisq")


dev.new()
plot(groundhog)
lines(groundhog$Year, predict(groundhog.model, type="response"))