Using Your TI83/84 Calculator:
Linear Correlation and Regression
Elementary Statistics
Dr. Laura Schultz
This handout describes how to use your calculator for various linear correlation and regression
applications.
For illustration purposes, we will work with a data set consisting of the winning men’s
Olympic high jump heights (in inches) paired with the years those heights were attained.
To
simplify the regression equation, I have coded the Olympic year to be zero in 1900.
You can find
this data set in the Appendix at the end of this handout.
1.
Before we can get started, you will need to enter the men’s Olympic high jump data into your
calculator.
We will be using this data set for several different
applications, so it will be helpful to enter the data into named lists.
Press
Se
.
Insert a list by highlighting
L
1
and pressing
`d
.
Name this list
OLYR
and proceed to enter the yearcode data
into this list.
Insert another list named
JUMP
and enter the highjump
height data into this list.
Check over your lists to make sure you didn’t
enter any incorrect data values.
Note that each
OLYR
value must be
paired with the corresponding high
JUMP
height for that year.
2.
Generating a Scatterplot.
To get a sense of the data, start by
generating a scatterplot.
Press
`!
to access the
,
menu.
Make sure all the plots except
Plot1
are turned off, and then press
1
.
Select the first
Type
of plot.
At the
Xlist
prompt, enter the name of
the list containing the predictor variable; this variable will be assigned
to the
x
axis of the plot.
For this example, the
Xlist
is
OLYR
.
Enter
the name of the response variable at the
Ylist
prompt; the values in
this list will be plotted on the
y
axis.
The
Ylist
for this example is
JUMP
.
3.
Press
#9
to view the scatterplot.
There should be no line drawn
through the points on your plot; if there is a line, you will need to
press
!
and make sure all the equations are empty for
Plot1
.
(Select
any equation you need to clear and press
C
.)
What can you tell
from the scatterplot?
Does there appear to be a linear correlation
between
OLYR
and
JUMP
?
If so, is it positive or negative?
How
strong does the correlation appear to be?
4.
The next step is to find the linear correlation coefficient (
r
) and
determine whether there is a significant linear correlation between our
two variables.
The
LinRegTTest
function on your calculator
provides “onestop shopping” for answering these and other questions
relating to linear correlation and regression.
Press
S
and scroll
right to the
TESTS
menu.
Scroll down to
LinRegTTest
and press
e
. (
Note: This is menuitem
F
on a TI84 calculator, but it is
E
on
a TI83 calculator.
)
Copyright © 2007 by Laura Schultz.
All rights reserved.
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 Fall '07
 Jerome
 Statistics, Correlation, Linear Regression, Regression Analysis, Statistical hypothesis testing, Dr. Laura Schultz

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