Oct 3, 2007 08:40
16 yrs ago
English term
significance level
English to Russian
Science
Mathematics & Statistics
All statistical tests will be performed using two-sided tests with a significance level of 0.05.
Proposed translations
(Russian)
| 3 +8 | уровень значимости |
Kirill Semenov
|
| 4 | уровень значимости |
Evgeny Terekhin
|
| 4 | уровень достоверности |
Vanda Nissen
|
Change log
Oct 3, 2007 08:48: Maksym Nevzorov changed "Field" from "Medical" to "Science" , "Field (specific)" from "Medical (general)" to "Mathematics & Statistics"
Proposed translations
+8
1 min
Kirill Semenov
Ukraine
Ukraine
Native in Russian
Works in field
Ukraine
60+ books translated and published
Native in: Russian 
Works in: English to Russian, Russian
Related KudoZ points
:
90
4 KudoZ points awarded for this answer.
Comment: "Большое спасибо всем!"
3 mins
Evgeny Terekhin
United States
United States
Native in Russian
United States
ATA-certified: literary, medical, SEO
Native in: Russian
Works in: English to Russian, Russian to English, Ukrainian to English
уровень значимости
Для всех статистических тестов в качестве критерия статистической достоверности рассматривался уровень значимости более 0,95." . Наш комментарий. ...
www.biometrica.tomsk.ru/kk/index_3.htm
www.biometrica.tomsk.ru/kk/index_3.htm
2 mins
Vanda Nissen
Australia
Australia
Native in Russian
Australia
PhD in Linguistics, NAATI certified
Native in: Russian
Works in: English to Russian, Danish to Russian, Russian to English, and 5 more.
уровень достоверности
подходит
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Note added at 3 mins (2007-10-03 08:44:04 GMT)
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In traditional frequentist statistical hypothesis testing, the significance level of a test is the maximum probability, assuming the null hypothesis, that the statistic would be observed. Hence, the significance level is the probability that the null hypothesis will be rejected in error when it is true (a decision known as a Type I error, or "false positive").
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Note added at 3 mins (2007-10-03 08:44:04 GMT)
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In traditional frequentist statistical hypothesis testing, the significance level of a test is the maximum probability, assuming the null hypothesis, that the statistic would be observed. Hence, the significance level is the probability that the null hypothesis will be rejected in error when it is true (a decision known as a Type I error, or "false positive").
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