typical standard errors

USAGE SUMMARY

The phrase "typical standard errors" is correct and usable in written English.
It can be used in statistical contexts to refer to the common or expected standard errors associated with a particular analysis or dataset. Example: "The results of the regression analysis showed typical standard errors, indicating that the estimates were reliable."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

1 human-written examples

Typical standard errors are a few degrees for the off-diagonal phase and < 0.1 in logarithmic scale for the off-diagonal apparent resistivity.

Earth, Planets and Space

Human-verified similar examples from authoritative sources

Similar Expressions

59 human-written examples

In practice, using only 1.5 Kb, a cardinality of a one billion can be easily estimated with a typical standard error of about 2%.

EURASIP Journal on Information Security

This value can be regarded as a typical standard error in the estimation of ΔΔG [ 44].

BMC Genomics

These 1000 estimates provided the standard deviation of x i with the typical standard error = standard deviation divided by, where n is the number of bootstrapped sets.

Bioinformatics

1) Short Infusion Study Measured concentrations of Org 25435 from all subjects in the Short Infusion study are shown in Figure 4. Pharmacokinetic parameter estimates for the interim model, based on the Short Infusion study data only, are provided in Table 2. Data are typical values (standard error).

BMC Anesthesiology

A growing number of papers have documented the inadequacy of typical methods of obtaining standard errors when the number of treated units is small (see Moulton (1990), Wooldridge: Cluster-sample methods in applied econometrics: an extended analysis, unpublished, Donald and Lang (2007), Abadie et al. (2010), and Buchmueller et al. (2011)).

IZA Journal of Labor Economics

Population pharmacokinetic estimates (typical value ± standard error), based on the final covariate model, were clearance (CL: 0.407 ± 0.0103 L/day), apparent volumes of distribution in the central (V1: 3.29 ± 0.0679 L) and peripheral (V2: 4.13 ± 0.16 L) compartments, and intercompartment clearance (Q: 7.14 ± 0.489 L/day).

European Journal of Clinical Pharmacology

Analysis 1 produces larger standard errors than Analysis 2, which is consistent with the typical patterns observed in the analysis with measurement error models in the literature.

Journal of Statistical Distributions and Applications

Error bars represent standard errors.

Nature

Error bars indicate standard errors.

Nature

Error bars denote standard errors of mean.

Nature

Expert writing Tips

Best practice

When reporting statistical results, contextualize "typical standard errors" by comparing them to expected or acceptable ranges within your field to provide a clear benchmark for your audience.

Common error

Avoid assuming that "typical standard errors" are inherently acceptable. Always evaluate them against established benchmarks and consider their potential impact on the validity of your conclusions.

Linguistic Context

The phrase "typical standard errors" functions as a descriptive modifier in statistical and scientific writing. It characterizes the standard errors as being representative or common for a given context. Ludwig AI indicates this phrase is correct and usable in written English.

Expression frequency: Rare

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Academia

0%

Ludwig's WRAP-UP

In summary, "typical standard errors" is a phrase used in scientific and statistical writing to describe standard errors that are representative or common for a given context. As Ludwig AI confirms, the phrase is grammatically correct and usable. It serves the purpose of providing a benchmark for evaluating the magnitude of standard errors, helping readers assess whether the observed errors are within an expected range. It's important to use this phrase judiciously, ensuring that the context and comparisons are clear and relevant to the audience. While the phrase suggests a sense of normalcy, it should not be misinterpreted as an indicator of acceptability without further evaluation against established benchmarks.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

usual standard errors

Replaces "typical" with "usual", suggesting what is normally encountered or expected.

common standard errors

Substitutes "typical" with "common", indicating errors that frequently occur.

expected standard errors

Replaces "typical" with "expected", highlighting anticipated error magnitudes.

representative standard errors

Uses "representative" instead of "typical", implying errors that accurately reflect the overall error distribution.

normal standard errors

Employs "normal" to denote errors conforming to a standard or usual pattern.

average standard errors

Replaces "typical" with "average", focusing on the mean error value.

standard errors, as expected

Rephrases to emphasize the anticipation of certain error levels.

customary standard errors

Uses "customary" to indicate errors that are conventional or traditionally observed.

ordinary standard errors

Replaces "typical" with "ordinary", suggesting errors that are unexceptional or unremarkable.

general standard errors

Uses "general" to describe errors that are broadly applicable or not specific to a particular case.

FAQs

How do I interpret "typical standard errors" in research?

Interpreting "typical standard errors" involves comparing them to established norms within your field. A typical error might be acceptable if it aligns with previous research but requires scrutiny if it deviates significantly. Consider its effect on the precision and reliability of your findings.

What does it mean when my standard errors are larger than "typical standard errors"?

Larger-than-"usual standard errors" suggest greater uncertainty in your estimates. Investigate potential causes, such as small sample sizes, high variability in the data, or model misspecification, and consider methods to reduce these errors.

Are there alternatives to using "typical standard errors" in statistical reports?

Yes, instead of "typical standard errors", you can use phrases like "common standard errors", "expected standard errors", or "average standard errors" depending on the specific context and emphasis you want to convey.

How do "typical standard errors" compare to confidence intervals?

"Typical standard errors" reflect the precision of a point estimate, while confidence intervals provide a range within which the true population parameter is likely to fall. Standard errors are used to calculate confidence intervals, and both measures help assess the uncertainty associated with statistical estimates.