Search results
Results From The WOW.Com Content Network
If set to "y" or "yes", the test case is made collapsible. The test case is collapsed and given a green heading if all the template outputs are the same. If any of the template outputs differ, the test case is expanded and given a yellow heading. See #Collapsible test cases for other parameters which only work when _collapsible is enabled.
Unpaired samples are also called independent samples. Paired samples are also called dependent. Finally, there are some statistical tests that perform analysis of relationship between multiple variables like regression. [1] Number of samples: The number of samples of data. Exactness: A test can be exact or be asymptotic delivering approximate ...
Example of A/B testing on a website. By randomly serving visitors two versions of a website that differ only in the design of a single button element, the relative efficacy of the two designs can be measured. A/B testing (also known as bucket testing, split-run testing, or split testing) is a user experience research method. [1]
Template:Test case nowiki, for templates with complex invocations; Template:Collapsible test case, to collapse test cases when the main and sandbox templates produce the same result; Note that all of these templates can produce collapsible test cases, but Template:Collapsible test case has this feature turned on by default. For detailed ...
Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Donate; Help; Learn to edit; Community portal; Recent changes; Upload file
Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Donate
Templates invoking Module:Template test case: Template:Test case – a generalised test case template; Template:Testcase rows – for a table of test cases arranged in rows; Template:Testcase table – for a table of test cases arranged in columns; Template:Collapsible test case – for test cases collapsed by default if the results are the same
In statistical hypothesis testing, a two-sample test is a test performed on the data of two random samples, each independently obtained from a different given population. The purpose of the test is to determine whether the difference between these two populations is statistically significant .