2.Tests (TEST)
Z
The
Test provides a variety of different standardization-based tests. They make it possible
to test whether or not a sample accurately represents the population when the standard
deviation of a population (such as the entire population of a country) is known from previous
Z
tests.
testing is used for market research and public opinion research that need to be
performed repeatedly.
Z
1-Sample
Test tests for unknown population mean when the population standard
deviation is known.
Z
2-Sample
Test tests the equality of the means of two populations based on independent
samples when both population standard deviations are known.
Z
1-Prop
Test tests for an unknown proportion of successes.
Z
2-Prop
Test tests to compare the propotion of successes from two populations.
t
The
Test tests the hypothesis when the population standard deviation is unknown. The
hypothesis that is the opposite of the hypothesis being proven is called the null hypothesis ,
while the hypothesis being proved is called the alternative hypothesis . The
applied to test the null hypothesis. Then a determination is made whether the null hypothesis
or alternative hypothesis will be adopted.
t
1-Sample
Test tests the hypothesis for a single unknown population mean when the
population standard deviation is unknown.
t
2-Sample
Test compares the population means when standard deviations are unknown.
t
Linear Reg
Test calculates the strength of the linear association of paired data.
!
2
Test tests hypothesis concerning the proportion of samples included in each of a number
of independent groups. Mainly, it generates cross-tabulation of two categorical variables
(such as yes, no) and evaluates the independence of these variables. It could be used, for
example, to evaluate the relationship between whether or not a driver has ever been
involved in a traffic accident and that person's knowledge of traffic regulations.
F
2-Sample
Test tests the hypothesis for the ratio of sample variances. It could be used, for
example, to test the carcinogenic effects of multiple suspected factors such as tobacco use,
alcohol, vitamin deficiency, high coffee intake, inactivity, poor living habits, etc.
ANOVA tests the hypothesis that the population means of the samples are equal when there
are multiple samples. It could be used, for example, to test whether or not different combina-
tions of materials have an effect on the quality and life of a final product.
One-Way ANOVA is used when there is one independent variable and one dependent
variable.
Two-Way ANOVA is used when there here are two independent variables and one depend-
ent variable.
The following pages explain various statistical calculation methods based on the principles
described above. Full details concerning statistical principles and terminology can be found
in any standard general statistics textbook.
6
t
-test is normally
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