average standard errors

USAGE SUMMARY

The phrase "average standard errors" is correct and usable in written English.
It can be used in statistical contexts when discussing the average of standard errors calculated from a set of data or estimates. Example: "The analysis revealed that the average standard errors for the regression coefficients were relatively low, indicating a high level of precision in the estimates."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

5 human-written examples

Four cross-validation prediction error parameters were taken into account: root-mean-square (RMS), mean standardized (MeanStan), root-mean-square standardized (RMSStan) and average standard errors (ASE) for geostatistical methods.

BMC Public Health

The average standard errors are 13.4% and 12.2% for anandamide and arachidonate respectively.

Biological Procedures Online

Average standard errors of r YD, u ^ were equal to 0.024, 0.021 and 0.021 in models MA, MG and MGD, respectively.

Genetics, Selection, Evolution

Where a group had been formed (as described above) by pooling values over different health states, average standard errors were used guaranteed to be greater than the true standard errors in the presence of (unknown) correlations between states.

British Medical Journal

ASE: Average standard errors; CI: Confidence interval; CLR: Conditional logistic regression; JEM: Job-exposure matrix; MIE: Mean index of exposure; PM: Pleural mesothelioma; RMSE: Root mean squared error; SDE: Standard deviation of the estimates; ULR: Unconditional logistic regression; WC: Weighted Cox model.

BMC Medical Research Methodology

Human-verified similar examples from authoritative sources

Similar Expressions

55 human-written examples

Results are expressed as average (standard error).

Intensive Care Medicine Experimental

Thus, only differences at or above one (average) standard error are considered as relevant in this paper.

Large-scale Assessments in Education

The scale bar shows ten times the average standard error of the estimated entries in the sample covariance matrix.

Rice

For France, the industry‐average firm effects displayed in Table A2 have an average standard error of 0.0027 (minimum standard error 0.0004, maximum standard error of 0.0246).

IZA Journal of Labor Economics

If the twelve sampling points are organized systematically, the average standard error is reduced to 0.06 units and the coefficient of variation to less than 0.03.

Agricultural and Forest Meteorology

Numerical detonation models were in good agreement with experimental results having an average standard error less than 3% for impulse predictions.

International Journal of Impact Engineering

Expert writing Tips

Best practice

When reporting "average standard errors", clearly specify the dataset or sample from which the standard errors were calculated to provide context for the reported value.

Common error

Avoid assuming that a low "average standard error" necessarily indicates high accuracy. It reflects the precision of the estimates within the sample, but doesn't account for other potential sources of error such as bias or confounding variables.

Linguistic Context

The phrase "average standard errors" functions as a descriptive statistical term. It is used to quantify the typical amount of error or variability associated with a set of statistical estimates, as shown in the examples provided by Ludwig.

Expression frequency: Rare

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Academia

0%

Ludwig's WRAP-UP

In summary, "average standard errors" is a phrase used in statistical contexts to describe the typical error associated with a set of estimates. Ludwig AI confirms its grammatical correctness, with usage primarily found in scientific sources. Although less common in general writing, understanding its use is crucial for interpreting research data. To avoid misinterpretations, make sure to specify the data from which the standard errors are calculated and remember that low "average standard errors" do not necessarily indicate accuracy, as precision only reflects a part of the entire process.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

mean standard errors

Replaces "average" with "mean", a synonym in statistical contexts, maintaining the core meaning.

typical standard errors

Substitutes "average" with "typical", suggesting a representative value of standard errors.

usual standard errors

Similar to "typical standard errors", using "usual" to indicate a common value.

representative standard errors

Emphasizes that the standard errors are indicative of a larger set.

overall standard error

Refers to a single, aggregated measure of standard error, rather than multiple individual errors.

pooled standard errors

Specifies that the standard errors have been combined or aggregated from multiple sources.

combined standard errors

Similar to "pooled standard errors", highlighting the aggregation of multiple standard errors.

typical error margin

Describes the average error range observed in a sample or set of measurements.

average uncertainty

Broader term reflecting the typical range of uncertainty.

general error level

Reflects the typical magnitude of errors in a given context.

FAQs

How do you calculate "average standard errors"?

To calculate "average standard errors", you typically sum the standard errors from a set of estimates and divide by the number of estimates. This provides a measure of the typical variability across those estimates.

When is it appropriate to use "average standard errors"?

"Average standard errors" are appropriate when summarizing the variability across multiple estimates or measurements. This provides a single value representing the typical precision of the individual estimates.

What does a high "average standard error" indicate?

A high "average standard error" suggests that, on average, the individual estimates have a wide range of potential values. This indicates lower precision and greater uncertainty in the estimates.

What's the difference between "average standard errors" and standard deviation?

"Average standard errors" represent the typical error in estimating a parameter, while standard deviation measures the spread of the data itself. The former relates to the precision of an estimate, the latter to the variability within a dataset.