Noun
/taɪp ðaɪ θriː ˈɛrər/
The term "type III error" refers to a specific kind of statistical error that occurs when researchers correctly reject a null hypothesis but do so for the wrong reason or based on incorrect assumptions about the data. This concept is less commonly discussed than type I and type II errors, which pertain to incorrect decisions about hypotheses.
In general, discussions about type III errors point to errors in interpreting the results of a study, misapplying statistical tests, or not properly understanding the framework within which the data were analyzed. The frequency of use for "type III error" is relatively low and is more likely to appear in academic, statistical, or specialized contexts than in everyday conversation.
In our analysis, we identified a type III error that led us to the wrong conclusions about the data.
В нашем анализе мы выявили ошибку типа III, которая привела нас к неверным выводам о данных.
Researchers should be cautious of type III errors when interpreting complex datasets.
Исследователям следует быть осторожными с ошибками типа III при интерпретации сложных наборов данных.
The discussion regarding type III error is crucial for understanding the implications of our findings.
Обсуждение ошибки типа III очень важно для понимания последствий наших выводов.
The phrase "type III error" is mainly used in academic and professional contexts and is not commonly found in idiomatic expressions. However, it is often discussed alongside other types of errors in statistical hypotheses, such as type I and type II errors. Here are some sentences that highlight its usage alongside these concepts:
Avoiding type III errors is just as important as preventing type I and type II errors in research practices.
Избегание ошибок типа III так же важно, как предотвращение ошибок типа I и II в исследовательской практике.
When presenting findings, make sure to clarify any potential type III errors to give a complete picture of the study's limitations.
Когда вы представляете результаты, убедитесь, что Clarify любые потенциальные ошибки типа III, чтобы дать полное представление о ограничениях исследования.
Understanding type III errors allows researchers to better navigate the complexities of hypothesis testing.
Понимание ошибок типа III позволяет исследователям лучше ориентироваться в сложностях тестирования гипотез.
The term "type III error" originates from the field of statistics, following the established nomenclature of error types. Type I errors refer to false positives while type II errors are about false negatives. The inclusion of "type III" corresponds to another dimension of error regarding the interpretation of statistical results. However, the specific origin of the phrase itself may not be well-documented, as it generally evolved in the context of academic discussions around statistical methodology.