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  2. Positive and negative predictive values - Wikipedia

    en.wikipedia.org/wiki/Positive_and_negative...

    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.

  3. Confusion matrix - Wikipedia

    en.wikipedia.org/wiki/Confusion_matrix

    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).

  4. Precision and recall - Wikipedia

    en.wikipedia.org/wiki/Precision_and_recall

    In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).

  5. How Do I Calculate the Net Present Value (NPV) on ... - AOL

    www.aol.com/finance/calculate-net-present-value...

    The post How to Calculate the Net Present Value (NPV) on Investments appeared first on SmartReads by SmartAsset. Net present value (NPV) represents the difference between the present value of cash ...

  6. Pre- and post-test probability - Wikipedia

    en.wikipedia.org/wiki/Pre-_and_post-test_probability

    In clinical practice, post-test probabilities are often just estimated or even guessed. This is usually acceptable in the finding of a pathognomonic sign or symptom, in which case it is almost certain that the target condition is present; or in the absence of finding a sine qua non sign or symptom, in which case it is almost certain that the target condition is absent.

  7. Likelihood ratios in diagnostic testing - Wikipedia

    en.wikipedia.org/wiki/Likelihood_ratios_in...

    Estimated change in probability: Based on table above, a likelihood ratio of 2.0 corresponds to an approximately +15% increase in probability. Final (post-test) probability: Therefore, bulging flanks increases the probability of ascites from 40% to about 55% (i.e., 40% + 15% = 55%, which is within 2% of the exact probability of 57%).

  8. How to calculate the present and future value of annuities - AOL

    www.aol.com/finance/calculate-present-future...

    Therefore, the future value of your regular $1,000 investments over five years at a 5 percent interest rate would be about $5,525.63. Note: This calculation assumes equal annual contributions and ...

  9. Template:DiagnosticTesting Diagram - Wikipedia

    en.wikipedia.org/wiki/Template:DiagnosticTesting...

    Positive predictive value (PPV), Precision = ⁠ Σ True positive / Σ Predicted condition positive ⁠ False discovery rate (FDR) = ⁠ Σ False positive / Σ Predicted condition positive ⁠ Predicted condition negative: False negative, Type II error: True negative: False omission rate (FOR) = ⁠ Σ False negative / Σ Predicted condition ...