User Manual

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5. Tests
The Z 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 tests.
Z
testing is used for market research and public opinion research, that need to be performed
repeatedly.
1-Sample
Z Test tests for the unknown population mean when the population standard
deviation is known.
2-Sample
Z Test tests the equality of the means of two populations based on independent
samples when both population standard deviations are known.
1-Prop
Z Test tests for an unknown proportion of successes.
2-Prop
Z Test tests to compare the proportion of successes from two populations.
The t 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
t Test is normally
applied to test the null hypothesis. Then a determination is made whether the null hypothesis
or alternative hypothesis will be adopted.
1-Sample
t Test tests the hypothesis for a single unknown population mean when the
population standard deviation is unknown.
2-Sample
t Test compares the population means when the population standard deviations are
unknown.
LinearReg
t Test calculates the strength of the linear association of paired data.
With the
χ
χ
2
test , a number of independent groups are provided and a hypothesis is tested
relative to the probability of samples being included in each group.
The
χ
χ
2
GOF test ( χ
2
one-way Test) tests whether the observed count of sample data fits
a certain distribution. For example, it can be used to determine conformance with normal
distribution or binomial distribution.
The
χ
χ
2
two-way test creates a cross-tabulation table that structures mainly two qualitative
variables (such as “Yes” and “No”), and evaluates the independence of the variables.
2-Sample F 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
combinations 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 are two independent variables and one dependent
variable.