# EXEMPLO 3.1

gpa1_data	<-	read.table("D:/_econometria/dados/datasets/GPA1.raw", header=TRUE, sep="", na.strings="NA", dec=".", strip.white=TRUE)
reg1		<-	lm(colGPA~hsGPA+ACT,data= gpa1_data)
summary(reg1)

# EXEMPLO 3.4
# R2


rm(list=ls(all=TRUE))
# EXEMPLO 3.2

wage_data		<- 	read.table("D:/_econometria/dados/datasets/WAGE1.raw", header=TRUE, sep="", na.strings="NA", dec=".", strip.white=TRUE)
attach(wage_data)

reg2			<-	lm(lwage~educ+exper+tenure)
summary(reg2)


rm(list=ls(all=TRUE))
# EXEMPLO 3.3
data_401		<- 	read.table("D:/_econometria/dados/datasets/401k.raw", header=TRUE, sep="", na.strings="NA", dec=".", strip.white=TRUE)
reg1			<-	lm(prate~mrate+age,data=data_401)
summary(reg1)


rm(list=ls(all=TRUE))
# EXEMPLO 3.5
crime1_data		<- 	read.table("D:/_econometria/dados/datasets/CRIME1.raw", header=TRUE, sep="", na.strings="NA", dec=".", strip.white=TRUE)
reg1			<-	lm(narr86~pcnv+ptime86+qemp86,data=crime1_data)
summary(reg1)


reg2			<-	lm(narr86~pcnv+avgsen+ptime86+qemp86,data=crime1_data)
summary(reg2)


rm(list=ls(all=TRUE))
# EXEMPLO 3.6
wage_data		<-	read.table("D:/_econometria/dados/datasets/WAGE1.raw", header=TRUE, sep="", na.strings="NA", dec=".", strip.white=TRUE)
attach(wage_data)

reg1<-lm(lwage~educ)
summary(reg1)