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The purpose of standards-based assessment [5] is to connect evidence of learning to learning outcomes (the standards). When standards are explicit and clear, the learner becomes aware of their achievement with reference to the standards, and the teacher may use assessment data to give meaningful feedback to students about this progress.
Predicted outcome value theory is an alternative to uncertainty reduction theory, which Charles R. Berger and Richard J. Calabrese introduced in 1975. Uncertainty reduction theory states that the driving force in initial interactions is to collect information to predict attitudes and behaviors for future relationship development.
Predictive modelling uses statistics to predict outcomes. [1] Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place. [2]
The SOFA scoring system is useful in predicting the clinical outcomes of critically ill patients. [8] According to an observational study at an Intensive Care Unit (ICU) in Belgium, the mortality rate is at least 50% when the score is increased, regardless of initial score, in the first 96 hours of admission, 27% to 35% if the score remains unchanged, and less than 27% if the score is reduced. [9]
In project management, trend analysis is a mathematical technique that uses historical results to predict future outcome. This is achieved by tracking variances in cost and schedule performance. This is achieved by tracking variances in cost and schedule performance.
The core of predictive analytics relies on capturing relationships between explanatory variables and the predicted variables from past occurrences, and exploiting them to predict the unknown outcome. It is important to note, however, that the accuracy and usability of results will depend greatly on the level of data analysis and the quality of ...
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