#import the data set in csv form.
pntsprd<-read.csv("C:/Data/pntsprd.csv",header=T)

#run Linear Probability Models with Robust Standard Errors
myreg <-lm(sprdcvr ~ spread), vce(robust)
myreg <-lm(sprdcvr ~ spread+favhome+neutral+fav25+und25+fregion+uregion), vce(robust) 

#run the probit regression
myprobit <- glm(sprdcvr ~ favhome+neutral+fav25+und25+fregion+uregion, family=binomial(link = "probit"), data=pntsprd)
summary(myprobit)

#all variables appear to be insignificant so let use only the intercept
#and test it equal to 0.5 as would be expected in an efficient betting market
myprobit <- glm(sprdcvr ~ , family=binomial(link = "probit"), data=pntsprd)
summary(myprobit)


#run the logit regression
mylogit <- glm(sprdcvr ~ favhome+neutral+fav25+und25+fregion+uregion, family=binomial(link = "logit"), data=pntsprd)
summary(mylogit)

#all variables appear to be insignificant so let use only the intercept
#and test it equal to 0.5 as would be expected in an efficient betting market
mylogit <- glm(sprdcvr ~ , family=binomial(link = "logit"), data=pntsprd)
summary(mylogit)