Statistical ratios | Statistical classification

Sensitivity and specificity

Sensitivity and specificity mathematically describe the accuracy of a test which reports the presence or absence of a condition. Individuals for which the condition is satisfied are considered "positive" and those for which it is not are considered "negative". * Sensitivity (true positive rate) refers to the probability of a positive test, conditioned on truly being positive. * Specificity (true negative rate) refers to the probability of a negative test, conditioned on truly being negative. If the true condition can not be known, a "gold standard test" is assumed to be correct. In a diagnostic test, sensitivity is a measure of how well a test can identify true positives and specificity is a measure of how well a test can identify true negatives. For all testing, both diagnostic and screening, there is usually a trade-off between sensitivity and specificity, such that higher sensitivities will mean lower specificities and vice versa. If the goal is to return the ratio at which the test identifies the percentage of people highly likely to be identified as having the condition, the number of true positives should be high and the number of false negatives should be very low, which results in high sensitivity. This is especially important when the consequence of failing to treat the condition is serious and/or the treatment is very effective and has minimal side effects. If the goal is to return the ratio at which the test identifies the percentage of people highly likely to be identified as not having the condition, the number of true negatives should be high and the number of false positives should be very low, which results in high specificity. That is, people highly likely to be excluded by the test. This is especially important when people who are identified as having a condition may be subjected to more testing, expense, stigma, anxiety, etc. The terms "sensitivity" and "specificity" were introduced by American biostatistician Jacob Yerushalmy in 1947. (Wikipedia).

Sensitivity and specificity
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Ever wandered how to calculate sensitivity, specificity, positive and negative predictive values or odds ratios or even simply what these terms mean? Watch this short lecture.

From playlist Medical Statistics

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From playlist Learning medical statistics with python and Jupyter notebooks

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Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is and give examples of the specificity of a test. The sensitivity of a test indicates the probability that the subject will have a NEGATIVE result when the subject is actually NEGATIVE.

From playlist PROB & STATS 4 BAYES THEOREM

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Sensitivity (Electrical Engineering)

https://www.patreon.com/edmundsj If you want to see more of these videos, or would like to say thanks for this one, the best way you can do that is by becoming a patron - see the link above :). And a huge thank you to all my existing patrons - you make these videos possible. In this video

From playlist Advanced Circuit Design

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Prob & Stats - Bayes Theorem (2 of 24) What is the Sensitivity of a Test?

Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is and give examples of the sensitivity of a test. The sensitivity of a test indicates the probability that the subject will have a POSITIVE result when the subject is actually POSITIVE.

From playlist PROB & STATS 4 BAYES THEOREM

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04 1 Local Sensitivity Analysis

Local sensitivity analysis

From playlist QUSS GS 260

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Overview of various methods for sensitivity analysis in the UQ of subsurface systems

From playlist Uncertainty Quantification

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04-2 Sensitivity Analysis Global

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From playlist QUSS GS 260

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Machine Learning Fundamentals: Sensitivity and Specificity (old version)

NOTE: This video has been updated. Please watch the new version: https://youtu.be/vP06aMoz4v8 In this StatQuest we talk about Sensitivity and Specificity - to key concepts for evaluating Machine Learning methods. These make it easier to choose which method is best for your data. NOTE: At

From playlist StatQuest

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Machine Learning Fundamentals: Sensitivity and Specificity

In this StatQuest we talk about Sensitivity and Specificity - to key concepts for evaluating Machine Learning methods. These make it easier to choose which method is best for your data. For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you

From playlist StatQuest

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VassarStats - Clinical Block 1 Example

Lecturer: Dr. Erin M. Buchanan Missouri State University Spring 2017 This video covers the concepts and how to calculate: prevalence, sensitivity, specificity, likelihood ratios, and ROC curves. Lecture materials and assignments available at statisticsofdoom.com. https://statisticsofdo

From playlist Advanced Statistics Videos

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Test Characteristics: How Accurate was that Test?

Does a positive test mean that you have a disease? Does a negative test mean you're healthy? Unfortunately, the answer to both these questions isn't a definitive "yes". How good a test is depends on it's sensitivity and specificity. Learn about both, and why understanding these test charac

From playlist Healthcare Triage

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3.2.8 Introduction to Logistical Regression - Video 5: Thresholding

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From playlist MIT 15.071 The Analytics Edge, Spring 2017

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From playlist Cool Math Series

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Model Metrics includes specific coverage of: – The importance of metrics beyond accuracy for building effective models. – Coverage of sensitivity and specificity and their importance for building effective binary classification models. – The importance of feature engineering for building

From playlist Introduction to Text Analytics with R

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Sensitivity Versus Block Sensitivity I - Hao Huang

Hao Huang University of California, Los Angeles; Member, School of Mathematics March 12, 2013 There are two important measures of the complexity of a boolean function: the sensitivity and block sensitivity. Whether or not they are polynomial related remains a major open question. In this t

From playlist Mathematics

Related pages

False positive rate | Receiver operating characteristic | Contingency table | False alarm | Sensitivity index | Evaluation of binary classifiers | Brier score | Harmonic mean | Youden's J statistic | Hit rate | Confusion matrix | Normal distribution | Statistical hypothesis testing | False positive paradox | Detection theory | F-score | Type I and type II errors | Prevalence | Binomial proportion confidence interval | Statistic | Uncertainty coefficient | Cumulative accuracy profile | Statistical significance