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EXST 7003 Lab 10
Fall 2011
EXST 7003, Lab 10:
Simple Linear Regression
Week of:
November 14
th
18
th
DUE:
November 29
th
(Section 1)
December 2
th
(Section 2 and 3)
In the previous labs, our objective was to sample from one or more populations and to compare
certain parameters either with each other or with a specified value. In a regression analysis, the
objectives are slightly different. The purpose of a regression analysis is to observe sample
measurements taken on different variables, called
factors
or
independent
variables, and to
examine the relationship between these variables and a
response
or
dependent
variable. This
relationship is then expressed as a statistical model called the regression model.
Suppose that a response variable Y can be predicted by a linear function of a regressor variable
X. You can estimate
β
0
, the intercept, and
β
1
, the slope, in
•
i
i
i
X
Y
ε
β
+
+
=
1
0
for the observations
1, 2, .
.., n. Fitting this model with the REG procedure requires only the
following MODEL statement, where
y
is the outcome variable and
x
is the regressor variable.
=
i
proc reg;
model y=x;
run;
For example, you might use regression analysis to find out how well you can predict a child's
weight if you know that child's height. The following data are from a study of nineteen children.
Height and weight are measured for each child.
title 'Simple Linear Regression';
data Class;
input Name $ Height Weight Age @@;
datalines;
Alfred
69.0 112.5 14
Alice
56.5
84.0 13
Barbara 65.3
98.0 13
Carol
62.8 102.5 14
Henry
63.5 102.5 14
James
57.3
83.0 12
Jane
59.8
84.5 12
Janet
62.5 112.5 15
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This note was uploaded on 12/28/2011 for the course EXST 7003 taught by Professor Moser,e during the Fall '08 term at LSU.
 Fall '08
 Moser,E

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