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Question & Answer
Choose the Best Answer
Higher specificity always leads to higher statistical significance.
Low specificity can result in misleading statistical significance and impact the sensitivity of predictors.
Statistical significance is unrelated to the sensitivity and specificity of predictors.
Increased sensitivity of predictors automatically improves specificity and statistical significance.
Understanding the Answer
Let's break down why this is correct
Low specificity means many false positives. Other options are incorrect because Higher specificity does not automatically raise statistical significance; Statistical significance is affected by specificity.
Key Concepts
Sensitivity of Predictors
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Deep Dive: Sensitivity of Predictors
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Definition
The sensitivity of a predictor measures its responsiveness to changes in input features. Insensitive predictors exhibit stability in their predictions when inputs are close. Sensitivity is crucial for generalization and performance, especially with limited training data.
Topic Definition
The sensitivity of a predictor measures its responsiveness to changes in input features. Insensitive predictors exhibit stability in their predictions when inputs are close. Sensitivity is crucial for generalization and performance, especially with limited training data.
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