Number of Test Cases

There are many numbers of test cases present in the statistics. These test cases are identified by the hypothesis and distribution functions. First we are going to see the number of  general test cases .

Number of general test cases.:

The statistical includes the different types of test methods. They are elucidating as follows.

Statistical test

A conclusion function that receive its values in the set of hypotheses.

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Consistent test

When reflect on the possessions of a test as the sample size produce, a test is said to be consistent if, for a permanent range of test, the power next to any permanent unusual approach 1 in the limit.

Unbiased test

For a particular substitute hypothesis, a test is said to be unbiased when the probability of refuse the null hypothesis is not fewer than the significance level when the substitute is right and is fewer than or identical to the significance level when the null hypothesis is right

Size / Significance level of a test (α)

For uncomplicated hypotheses, the test's probability of imperfectly refuse the null hypothesis. The rate of  false positive For complex hypotheses is the superior bound of the probability of refuse the null hypothesis above all cases covered by the null hypothesis
Number of Powerful Test Cases.:

Power of a test (1 − β)

The test's probability of properly eliminate the null hypothesis. The auxiliary of the false negative rate, β.

Most powerful test

A individual range or significance level, the test among the uppermost power.

Uniformly most powerful test (UMP)

A test among the maximum power for the entire values of the parameter is tested.
Number of Test Cases in the Distribution.

F- Test

The F- Test is primarily utilize to evaluate the statistical expression of data set that is fit into the data set with the desire to  finds the finest fit population from the sample data .F- Test analysis is the one of the statistical applications of F- distribution.

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Z- Test

A Z-test is the another different type of statistical test method which the distribution of the test statistic under the null hypothesis can be approximated by a normal distribution

T- test:

It is a different type of test method. It is foundation on the T- distribution. It is used to test for distinction among the two means

Chi-square test:

It is the different statistical hypothesis test method. If the null hypothesis of chi-square distribution is true then it is called the chi-square test.