Casio SERIES FX-9860G - Manual (Page 314)

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6-5 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.
χ
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 traffi c accident and that person’s knowledge of traffi c regulations.
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 defi ciency, 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 fi nal 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.
6-5-1
Tests