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Definition Positive predictive value (PPV) The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.
DISC assessment. DISC assessments are behavioral self-assessment tools based on psychologist William Moulton Marston's DISC emotional and behavioral theory, first published in 1928. [1] These assessments aim to improve job performance by categorizing individuals into four personality traits: dominance, inducement, submission, and compliance .
Predictive analytics is a form of business analytics applying machine learning to generate a predictive model for certain business applications. As such, it encompasses a variety of statistical techniques from predictive modeling and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown ...
The Work Personality Index is a psychometric assessment that measures personality traits. It was designed by Dr. Donald Macnab and Shawn Bakker of Psychometrics Canada. The questionnaire is designed to identify personality traits that relate to work performance; it takes most people 10 minutes to complete. It was created for the applications of ...
Predictive validity. In psychometrics, predictive validity is the extent to which a score on a scale or test predicts scores on some criterion measure. [1] [2] For example, the validity of a cognitive test for job performance is the correlation between test scores and, for example, supervisor performance ratings.
In predictive analytics, a table of confusion (sometimes also called a confusion matrix) is a table with two rows and two columns that reports the number of true positives, false negatives, false positives, and true negatives. This allows more detailed analysis than simply observing the proportion of correct classifications (accuracy).
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