type ii error
RareTechnical
Definition
Meaning
In statistical hypothesis testing, a type II error (or false negative) is the failure to reject a false null hypothesis.
A failure to detect an effect, change, or condition that is actually present; a missed opportunity for detection or intervention due to insufficient evidence or statistical power.
Linguistics
Semantic Notes
This term is exclusively used in the context of formal statistical inference and related scientific/methodological fields. It exists as part of a complementary pair with 'type I error' (false positive).
Dialectal Variation
British vs American Usage
Differences
No significant differences in usage or spelling; it is a standardized scientific term.
Connotations
Conveys a negative outcome in research or testing, implying a flawed or underpowered experimental design.
Frequency
Extremely rare outside of statistics, data science, quality control, and academic research contexts.
Vocabulary
Collocations
Grammar
Valency Patterns
The study had a high risk of type II error.We must calculate the probability of a type II error (beta).Vocabulary
Synonyms
Strong
Neutral
Weak
Vocabulary
Antonyms
Phrases
Idioms & Phrases
- “On the wrong side of beta”
Usage
Context Usage
Business
Rare; might be used in data analytics or A/B testing discussions concerning failed detection of a profitable change.
Academic
Core term in statistics, psychology, medicine (clinical trials), and any empirical science.
Everyday
Virtually never used.
Technical
Primary context. Used in statistics, machine learning, hypothesis testing, and scientific methodology.
Examples
By Part of Speech
verb
British English
- The analysis may have type-II-errored, missing the true correlation.
- We need to ensure we don't type II error in this trial.
American English
- The test type-II-errored due to a small sample size.
- Be careful not to type II error when evaluating the new drug.
adjective
British English
- The type-II-error probability was unacceptably high.
- We calculated the type-II-error rate.
American English
- A type-II-error situation occurred in the experiment.
- The model's type-II-error risk is substantial.
Examples
By CEFR Level
- A type II error means the doctor said you were healthy when you were actually sick.
- Increasing the sample size reduces the probability of committing a type II error, thereby increasing the statistical power of the test.
Learning
Memory Aids
Mnemonic
Think 'II' as in 'I Ignored it' – you ignored an effect that was actually there.
Conceptual Metaphor
A FAILURE TO SOUND THE ALARM when a fire is actually present.
Watch out
Common Pitfalls
Translation Traps (for Russian speakers)
- Avoid literal translation. The correct Russian equivalent is 'ошибка второго рода' or 'ложноотрицательный результат'.
Common Mistakes
- Confusing it with type I error. Remember: Type II = 'Miss' (failed to detect truth). Type I = 'False Alarm'.
Practice
Quiz
What is the direct consequence of a type II error?
FAQ
Frequently Asked Questions
It is denoted by the Greek letter beta (β).
They are inversely related for a fixed sample size; reducing the risk of one typically increases the risk of the other.
Statistical power is 1 – β. It is the probability of correctly rejecting a false null hypothesis, thus avoiding a type II error.
No, you cannot eliminate them completely without also making type I errors certain. You can only minimise the risk, often by increasing sample size or effect size.