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Higher-order thinking, also known as higher order thinking skills (HOTS), [1] is a concept applied in relation to education reform and based on learning taxonomies (such as American psychologist Benjamin Bloom's taxonomy). The idea is that some types of learning require more cognitive processing than others, but also have more generalized benefits.
Under-representation of one class in the outcome (dependent) variable. Suppose we want to predict, from a large clinical dataset, which patients are likely to develop a particular disease (e.g., diabetes). Assume, however, that only 10% of patients go on to develop the disease. Suppose we have a large existing dataset.
A multiple choice question, with days of the week as potential answers. Multiple choice (MC), [1] objective response or MCQ(for multiple choice question) is a form of an objective assessment in which respondents are asked to select only the correct answer from the choices offered as a list.
In statistics, the term higher-order statistics (HOS) refers to functions which use the third or higher power of a sample, as opposed to more conventional techniques of lower-order statistics, which use constant, linear, and quadratic terms (zeroth, first, and second powers).
In medicine and statistics, sensitivity and specificity mathematically describe the accuracy of a test that reports the presence or absence of a medical condition. If individuals who have the condition are considered "positive" and those who do not are considered "negative", then sensitivity is a measure of how well a test can identify true ...
Though there are many approximate solutions (such as Welch's t-test), the problem continues to attract attention [4] as one of the classic problems in statistics. Multiple comparisons: There are various ways to adjust p-values to compensate for the simultaneous or sequential testing of hypotheses. Of particular interest is how to simultaneously ...
Because of the central limit theorem, many test statistics are approximately normally distributed for large samples.Therefore, many statistical tests can be conveniently performed as approximate Z-tests if the sample size is large or the population variance is known.
Order statistics have a lot of applications in areas as reliability theory, financial mathematics, survival analysis, epidemiology, sports, quality control, actuarial risk, etc. There is an extensive literature devoted to studies on applications of order statistics in these fields.