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Features are the primary measurable operating characteristics of a product, while performance comes second.
Type II Error
The error made when a test fails to reject a false null hypothesis, often denoted by beta (β).
Type I Error
The error that occurs when a true null hypothesis is incorrectly rejected, falsely indicating a statistically significant effect.
Type I Error
The error of rejecting a true null hypothesis, also known as a "false positive" error.
Type II Error
Failing to detect an effect or difference that exists because the null hypothesis was incorrectly accepted.
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