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  2. Pre- and post-test probability - Wikipedia

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

    Pre-test probability and post-test probability (alternatively spelled pretest and posttest probability) are the probabilities of the presence of a condition (such as a disease) before and after a diagnostic test, respectively. Post-test probability, in turn, can be positive or negative, depending on whether the test falls out as a positive test ...

  3. Likelihood ratios in diagnostic testing - Wikipedia

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

    Likelihood ratios in diagnostic testing. In evidence-based medicine, likelihood ratios are used for assessing the value of performing a diagnostic test. They use the sensitivity and specificity of the test to determine whether a test result usefully changes the probability that a condition (such as a disease state) exists.

  4. Positive and negative predictive values - Wikipedia

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

    The positive and negative predictive values (PPV and NPV respectively) are the proportions of positive and negative results in statistics and diagnostic tests that are true positive and true negative results, respectively. [1] The PPV and NPV describe the performance of a diagnostic test or other statistical measure.

  5. Posterior probability - Wikipedia

    en.wikipedia.org/wiki/Posterior_probability

    Posterior probability is a conditional probability conditioned on randomly observed data. Hence it is a random variable. For a random variable, it is important to summarize its amount of uncertainty. One way to achieve this goal is to provide a credible interval of the posterior probability.

  6. P–P plot - Wikipedia

    en.wikipedia.org/wiki/P–P_plot

    P–P plot. In statistics, a P–P plot (probabilityprobability plot or percent–percent plot or P value plot) is a probability plot for assessing how closely two data sets agree, or for assessing how closely a dataset fits a particular model. It works by plotting the two cumulative distribution functions against each other; if they are ...

  7. Evaluation of binary classifiers - Wikipedia

    en.wikipedia.org/wiki/Evaluation_of_binary...

    As such, it compares estimates of pre- and post-test probability. In total ignorance, one can compare a rule to flipping a coin (p0=0.5). This measure is prevalence-dependent. If 90% of people with COVID symptoms don't have COVID, the prior probability P(-) is 0.9, and the simple rule "Classify all such patients as COVID-free." would be 90% ...

  8. Voynich manuscript - Wikipedia

    en.wikipedia.org/wiki/Voynich_manuscript

    Material: vellum: Size: ≈ 23.5 cm × 16.2 cm × 5 cm (9.3 in × 6.4 in × 2.0 in) Format: One column in the page body, with slightly indented right margin and with paragraph divisions, and often with stars in the left margin; [12] the rest of the manuscript appears in the form of graphics (i.e. diagrams or markings for certain parts related to illustrations), containing some foldable parts

  9. Post-test odds - Wikipedia

    en.wikipedia.org/wiki/Post-test_odds

    Post-test odds may refer to: Bayes' theorem in terms of odds and likelihood ratio. Post test odds as related to pre- and post-test probability. Category: Disambiguation pages.