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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.
Test management tools give teams the ability to consolidate and structure the test process using one test management tool, instead of installing multiple applications that are designed to manage only one step of the process. Test management tools allow teams to manage test case environments, automated tests, defects and project tasks.
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Teachers may also submit student papers to Turnitin.com as individual files, by bulk upload, or as a ZIP file. Teachers can further set assignment-analysis options so that students can review the system's "originality reports" before they finalize their submission. A peer-review option is also available.
This is an accepted version of this page This is the latest accepted revision, reviewed on 13 January 2025. Educational assessment For other uses, see Exam (disambiguation) and Examination (disambiguation). Cambodian students taking an exam in order to apply for the Don Bosco Technical School of Sihanoukville in 2008 American students in a computer fundamentals class taking an online test in ...
The parametric equivalent of the Kruskal–Wallis test is the one-way analysis of variance (ANOVA). A significant Kruskal–Wallis test indicates that at least one sample stochastically dominates one other sample. The test does not identify where this stochastic dominance occurs or for how many pairs of groups stochastic dominance obtains.
The assignment problem consists of finding, in a weighted bipartite graph, a matching of maximum size, in which the sum of weights of the edges is minimum. If the numbers of agents and tasks are equal, then the problem is called balanced assignment, and the graph-theoretic version is called minimum-cost perfect matching.
The binomial test is useful to test hypotheses about the probability of success: : = where is a user-defined value between 0 and 1.. If in a sample of size there are successes, while we expect , the formula of the binomial distribution gives the probability of finding this value: