Definition of sampling error in English:

sampling error

noun

mass nounStatistics

Error in a statistical analysis arising from the unrepresentativeness of the sample taken.
〔统计〕抽样误差
a percentage of the total variation is attributable to sampling error
Example sentencesExamples
- In addition to these caveats, sampling error due to analysis of an inadequate sample volume can also lead to a false-negative test result.
- This is because the statistical sampling error of the phase is inversely related to the squared coherence.
- A search for moderators was pursued only if less than 60% of the variation of observed coefficients could be explained by a combination of sampling error and measurement error.
- As with other statistical techniques, sampling errors can affect the parameters of the data spectrum, which are just estimates of true but unknown population data.
- As we assumed excess variability to be due to both sampling error and random differences across studies, we fitted the data to a random effects model, which provides more conservative estimates than a fixed effects model.

Definition of sampling error in US English:

sampling error

nounˈsæmp(ə)lɪŋ ˈɛrər

Statistics

Error in a statistical analysis arising from the unrepresentativeness of the sample taken.
〔统计〕抽样误差
a percentage of the total variation is attributable to sampling error
Example sentencesExamples
- This is because the statistical sampling error of the phase is inversely related to the squared coherence.
- In addition to these caveats, sampling error due to analysis of an inadequate sample volume can also lead to a false-negative test result.
- A search for moderators was pursued only if less than 60% of the variation of observed coefficients could be explained by a combination of sampling error and measurement error.
- As with other statistical techniques, sampling errors can affect the parameters of the data spectrum, which are just estimates of true but unknown population data.
- As we assumed excess variability to be due to both sampling error and random differences across studies, we fitted the data to a random effects model, which provides more conservative estimates than a fixed effects model.

单词	sampling error
释义	Definition of sampling error in English: sampling error noun mass nounStatistics Error in a statistical analysis arising from the unrepresentativeness of the sample taken. 〔统计〕抽样误差 a percentage of the total variation is attributable to sampling error Example sentencesExamples In addition to these caveats, sampling error due to analysis of an inadequate sample volume can also lead to a false-negative test result. This is because the statistical sampling error of the phase is inversely related to the squared coherence. A search for moderators was pursued only if less than 60% of the variation of observed coefficients could be explained by a combination of sampling error and measurement error. As with other statistical techniques, sampling errors can affect the parameters of the data spectrum, which are just estimates of true but unknown population data. As we assumed excess variability to be due to both sampling error and random differences across studies, we fitted the data to a random effects model, which provides more conservative estimates than a fixed effects model. Definition of sampling error in US English: sampling error nounˈsæmp(ə)lɪŋ ˈɛrər Statistics Error in a statistical analysis arising from the unrepresentativeness of the sample taken. 〔统计〕抽样误差 a percentage of the total variation is attributable to sampling error Example sentencesExamples This is because the statistical sampling error of the phase is inversely related to the squared coherence. In addition to these caveats, sampling error due to analysis of an inadequate sample volume can also lead to a false-negative test result. A search for moderators was pursued only if less than 60% of the variation of observed coefficients could be explained by a combination of sampling error and measurement error. As with other statistical techniques, sampling errors can affect the parameters of the data spectrum, which are just estimates of true but unknown population data. As we assumed excess variability to be due to both sampling error and random differences across studies, we fitted the data to a random effects model, which provides more conservative estimates than a fixed effects model.
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