Download Examples with Stats List Editor for TI-89

Examples Using the Stats/List
Editor with the TI-89 PLUS
Wm. J. Larson, [email protected], International School of Geneva
upper value = 1
To enter Stats/List Editor key  APPS
Deg of Freedom = 6
ENTER. The Stats/List Editor screen has
Auto-scale Yes
four columns labeled list1 to list4. Mostly
ENTER, ENTER
however we will be using the F1 to F7
buttons at the top.
The result is P(-1  t  1 and df = 6) =
After leaving Stats/List Editor, for example
.644, Which is 4% less than the normal
after looking at the GRAPH screen or the
Cdf above.
HOME screen, you will need to key 
APPS ENTER again to reenter Stats/List
ZInterval
Editor.
Example Calculate a confidence interval for 
using  = 5,  = 50, n = 25 and the desired
Normal Cdf
confidence level = 95%.
Example For a normal distribution calculate
Key F7 Ints
[Notice that Stats/List editor can calculate
P(x > 27| = 23,  = 2).
Key F5 Distr
the confidence interval for seven
[Notice that Statistics/List editor can
different cases.]
calculate the Pdf (probability distribution
Key 1: ZInterval.
function) & Cdf (cumulative probability
Choose the Data Input Method = Stats,
distribution function) for seven different
since n,  and  are already known,
distributions and can draw (Shade) and
ENTER
find the inverse for four of them.]
Input
Key 4: Normal Cdf
=5
lower value = 27
 = 50
upper value = 
n = 25
 = 23
C Level = .95
=2
press ENTER
Press ENTER, ENTER.
The result is C Int {48.04, 51.96}, ME (the
The result is P(x > 27| = 23,  = 2) = Cdf
margin of error = z*/n) = 1.96
= 0.0228
Example For a normal distribution calculate
T-Test
P(21 < x < 25| = 23,  = 2).
Example Test the hypothesis Ho: o = 10
Key F5 Distr, 4: Normal Cdf
with Ha: o  10 using the data {8, 8, 9, 9,
Enter
10, 11} using the t-distribution.
lower value = 21
Key HOME
upper value = 25
There are two ways to fill a list. We’ll use
 = 23
one method here & the other method
=2
below.
Press ENTER, ENTER
In the HOME screen key {8, 8, 9, 9, 10, 11}
The result is P(21 < x < 25| = 23,  = 2) =
STO VAR-LINK (2nd - ) List1 ENTER,
Cdf = 0.683, which agrees with the 68ENTER
95-99.7 rule.
Key  APPS ENTER
Notice that our data is now in list1.
F6 Tests 2: T-Test
Shade t
Choose the Data Input Method. Since we
Example Draw the Student t Distribution
want to use the data we just entered,
function and calculate the probability of
choose Data.
-1  t  1 with df (degrees of freedom) = 6.
Input o = 10
Key F5 Distr 1: Shade 2: Shade t.
List = VAR-LINK list1
lower value = -1
Freq = 1 (since each data point occurs once)
Choose the alternative hypothesis  o
Results: choose Draw, ENTER
The result is the t distribution with the tails
shaded, t = -1.746 and the P-value =
.141. So at the 10% level Ho cannot be
rejected.
[Calculate would have displayed the input
values plus t, the P-value, df, , Sx and
n.]
Linear Regression & a
Scatterplot
Example Fit the following data to a straight
line. Report the equation of the line, r² and
r. Plot the equation on top of the data. Make
a list of residuals.
1
2
3
4
5
x
23
24
25
24
27
y
Key  APPS ENTER
In the list screen scroll up and right to an
unnamed list. Key enter, type xlist and
enter 1, 2, 3, 4, 5, 6, 7, 8, 9, 10. Scroll
right to the next unnamed list. Key
ENTER, type ylist (to name the list) and
enter 23, 24, 25, 24, 27, 28, 30, 29, 35,
33.
To get the list of residuals set F1 Tools 9:
Format ResultsEditor to Yes.
Key F4 Calc 3: Regressions.
[Note that 11 Stats/List editor does 11
different kinds of regression.]
Choose 1: LinReg(a+bx)
Key X list = xlist, Y list = ylist
Store RegEQ to y1(x) (So that you can plot
the fitted line on top of your scatterplot.)
Freq =1 (Since each data point occurs
once.)
Key ENTER
The result is a = 20.9333, b = 1.24848, r² =
.8832, r = .9398, so the line is a fairly
good fit to the data.
Note that the residuals are in a list called
resid to the right of ylist, ready to be
displayed as a scatterplot.
Key F2 Plots 1: Plot Setup
Highlight Plot 1
Key F1 Define
Choose Plot Scatter
Note that there are 4 other kinds of plots.
6 Select Mark
7
8 (or whatever
9
10 like)
cross
you
28Key x =
30xlist, y 29
35
33
= ylist
Freq and Categories = No.
ENTER
Go to the Y = screen by keying Y = ( F1).
As we expected, the regression equation is
stored as y1 = 20.933 +1.248.
Go to the GRAPH screen by keying
GRAPH ( F3).
Key F2 Zoom 9:ZoomData. There’s the
data and the line. (F3 Trace ► or ◄ will
read out each data point. ▲ or ▼ will
take you back and forth between the
scatterplot and the regression line.)