Linked from

The 10 pages that link to Type I and type II errors, each with the reason it gives.

• Signal detection theoryRelated: False alarms and misses are the detection-theory counterparts of these errors.

• Limit of detectionRelated: Detection limits balance false alarms against missed analyte signals.

• False negativeNarrower topic: In hypothesis testing, a false negative corresponds to a type II error under the usual setup.

• Frequentist statisticsRelated: Their repeated-sampling rates are central criteria for evaluating frequentist tests.

• Egon PearsonRelated: Their theory weighs these distinct mistakes when selecting a test.

• Frequentist probabilityRelated: Their long-run rates are central performance measures for frequentist tests.

• Jerzy NeymanRelated: Neyman’s framework treats both errors as properties to control.

• Null hypothesis significance testingRelated: The decision rule trades off these two kinds of incorrect conclusion.

• Frequentist inferenceRelated: These error rates express the costs frequentist testing controls over repeated use.

• Sample size determinationRelated: Chosen error tolerances directly shape power-based sample size.