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Stat 371 Assignment 3 Spring 2010
Due
in class: Tuesday June 29
The purpose of this question is to review some of the tools used to assess the fit of a
model and to look for outliers in the data set. To do so we use an artificial example
with 50 observations on a response variate
y
and two explanatory variates
x
1
and
x
2
.
The data are stored in the file
ass3q1.txt
available on the course web page. The goal
of the investigation is to predict
y
when
x
x
12
15
15
=
=
,
. Start by fitting the model
y
x
x
r
=+
+
+
β
01
2
.
a)
Use plots of the estimated residuals and qq plots of the standardized residuals
to
determine if other terms (e.g. squares and products) or a transformation is needed.
To create a nice format for your plots, you might like to use the R code
par(mfrow=c(n,m))
where you select integers n and m. This creates an
n x m
array for
the next
nm
plots you create.
b)
Decide on a final form for the model.
c)
Examine the studentized residuals for your model. Do you see any evidence of
outliers in the ydirection?
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This note was uploaded on 05/12/2011 for the course STAT 371 taught by Professor Ahmed during the Fall '09 term at Waterloo.
 Fall '09
 AHMED

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