Texas Instruments TINSPIRE User Manual

Using Lists & Spreadsheet 587
Linear Reg t Test (LinRegtTest) computes a linear regression on the
given data and a
t test on the value of slope b and the correlation
coefficient r for the equation y=a+bx. It tests the null hypothesis H
0
: b=0
(equivalently, r=0) against one of the alternatives below.
•H
a
: bƒ0 and rƒ0
•H
a
: b<0 and r<0
•H
a
: b>0 and r>0
Multiple Reg Tests (MultRegTest) computes a linear regression on
the given data, and provides the F test statistic for linearity.
Refer to the TI-Nspire™ Reference Guide for information about
MultRegTests.
ANOVA (ANOVA) computes a one-way analysis of variance for
comparing the means of two to 20 populations. The ANOVA procedure
for comparing these means involves analysis of the variation in the
sample data. The null hypothesis H
0
: m
1
=m
2
=...=m
k
is tested against the
alternative H
a
: not all m
1
...m
k
are equal.
The ANOVA test is a method of determining if there is a significant
difference between the groups as compared to the difference occurring
within each group.
This test is useful in determining if the variation of data from sample-to-
sample shows a statistically significant influence of some factor other
than the variation within the data sets themselves. For example, a box
buyer for a shipping firm wants to evaluate three different box
manufacturers. He obtains sample boxes from all three suppliers. ANOVA
can help him determine if the differences between each sample group
are significant as compared to the differences within each sample group.
ANOVA 2-Way (ANOVA2way) computes a two-way analysis of
variance for comparing the means of two to 20 populations. A summary
of results is stored in the
stat.results variable.
The two-way ANOVA analysis of variance examines the effects of two
independent variables and helps to determine if these interact with
respect to the dependent variable. (In other words, if the two
independent variables do interact, their combined effect can be greater
than or less than the impact of either independent variable additively.)
This test is useful in evaluating differences similar to the ANOVA analysis
but with the addition of another potential influence. To continue with
the ANOVA box example, the two-way ANOVA might examine the
influence of box material on the differences seen.

Texas Instruments TINSPIRE Specifications

General

Brand	Texas Instruments
Model	TINSPIRE
Category	Calculator
Language	English