#read data
D <- read.table("ozbmi2.txt"¯,header=TRUE)

#write data
write.table(D, "newdata.txt"¯,se="\t"¯)

#list the variables in D
	names(D)
# dimensions of D
	dim(D)
# print the first 10 rows of D
	head(D, n=10)
#referring to variables in D
	#format is Object$variable
	head(D$age, n=10)

#You can make new variables within an existing object 
	D$newage<- D$age*100
#Or overwrite a variable
	D$age<- D$age*100
#Or recode a variable
	#D$catage <- ifelse(D$age > 30, 
	c("older"), c("younger")) 

#Mean and variance
	mean(D$age, na.rm =TRUE)
	var(D$age , na.rm =TRUE)

#A bit more info
	summary(D$age)
	summary(D$age[which(D$agecat==1)])
#What about a categorical variable
	table(D$agecat)
	table(D$agecat,D$zyg)

#typing D$ is getting annoying so we can attach the data
	attach(D)
	table(agecat,zyg)
	#detach(D)
#Correlations anyone?
	cor(wt1,bmi1, use="complete")
	cor(ht1,bmi1, use="complete")


#Multiple Linear Regression
	fit <- lm(bmi1 ~ age + zyg, data=D)
	summary(fit) 
# Other useful functions 
	coefficients(fit) # model coefficients
	confint(fit, level=0.95) # CIs for model parameters 
	anova(fit) # anova table 
	vcov(fit) # covariance matrix for model parameters 


#Histogram
#basic
	hist(age)
#basic
	hist(age, breaks=12, col='red')
# Add labels 
	hist(age, breaks=12, col='red', xlab='age in years',main='Histogram of age')



#Kernal density plot
d <- density(age, na.rm = "TRUE") # returns the density data
plot(d) # plots the results

##############################################################
#packages
install.packages()



#Kernal density plot by zyg?
library(sm)
# create value labels
zyg.f <- factor(zyg, levels= seq(1,5),
  labels = c("MZF", "MZM", "DZF", "DZM", "DZOS"))

# plot densities
sm.density.compare(age, zyg, xlab="Years")
title(main="Years by ZYG")

# add legend 
colfill<-c(2:(2+length(levels(zyg.f))))
legend(.8,3, levels(zyg.f), fill=colfill) 



# make a png file to hold the plot
png("zygdensity.png")

# create value labels
zyg.f <- factor(zyg, levels= seq(1,5),
  labels = c("MZF", "MZM", "DZF", "DZM", "DZOS"))
# plot densities
sm.density.compare(age, zyg, xlab="Yearsā€¯)
title(main="Years by ZYG")
# add legend via mouse click
colfill<-c(2:(2+length(levels(zyg.f))))
legend(.8,3, levels(zyg.f), fill=colfill) 

# close the png file to allow viewing
dev.off()


# 4 figures arranged in 2 rows and 2 columns
attach(mtcars)
par(mfrow=c(2,2))
plot(wt,mpg, main="Scatterplot of wt vs. mpg")
plot(wt,disp, type="n", main="wt vs disp")
	lines(sort(wt),sort(disp)) 
hist(wt, main="Histogram of wt")
boxplot(wt, main="Boxplot of wt")