#R-help to Exercise 8

 

 

# Read the data into a dataframe and give names to the variables:

cafe=read.table("http://www.uio.no/studier/emner/matnat/math/STK4900/data/exer3_1.dat")

names(cafe)=c("no","sale")

 

# Take a look at the data (make sure they correspond to those given in the exercise):

cafe

 

# Attach the dataframe (making the variables available):

attach(cafe)

 

 

# Make a plot of sale as a function of the number or dispensers:

plot(no,sale)

 

# Inspect the plot. How is the relation between the number of dispensers and the coffee sale?

 

 

# Fit a straight line and draw it on the plot:

linfit=lm(sale~no)

linfit

abline(linfit)

 

# How well does the straight line describe the relation between the number of dispensers and the coffee sale?

 

 

# Fit a second order polynomial (note that inside lm-command, we have to write the second order term inside I( ), (otherwise the sign ^  will be misinterpreted by R):

lm(sale~no+I(no^2))

 

# Compute and draw the fitted second order polynomial:

x=seq(0,7,0.1)

koef=lm(sale~no+I(no^2))$coef

koef

lines(x,koef[1]+koef[2]*x+koef[3]*x^2,lty=2)

 

# Do the straight line or the second order polynomial provide the best description of the relation between the number of dispensers and the coffee sale?