use a uniform average for

USAGE SUMMARY

The phrase "use a uniform average for" is correct and usable in written English.
It can be used when discussing the application of a consistent average value in calculations or assessments. Example: "In our analysis, we decided to use a uniform average for the data set to ensure consistency in our results."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified similar examples from authoritative sources

Similar Expressions

60 human-written examples

For PPI networks, we use a uniform distribution for the prior probabilities for all edges.

BMC Systems Biology

We use a uniform or triangular distribution between 0.2 and 2 for Pr.

BMC Evolutionary Biology

We use a uniform distribution.

EURASIP Journal on Wireless Communications and Networking

L. 105 178, § 3026(a)(2), substituted "using uniform categories" for "by uniform categories," and "and using a uniform system of accounts" for "and a uniform system of accounts and records".

Cornell University

In each setting, we used a uniform set of costs for purposes of comparison (Table 1).

eLife

Analyses using a uniform instead of a normal distribution yielded almost the same average time estimates and confidence interval width (not shown).

BMC Evolutionary Biology

We used a uniform prior for the analyses.

BMC Evolutionary Biology

In a sensitivity analysis we also used a uniform prior for the heterogeneity between trials.

British Medical Journal

Evaluation was performed using a uniform approach for all four data types, as follows.

Bioinformatics

We used a uniform prior for Θ between 0 and 0.1 and a sampling window of 0.01 on which to generate new proposals; for ℳ, we used a uniform prior between 0 and 1000 with a window of 100.

Evolutionary Applications

Analyses were conducted for 30 million generations using a uniform speciation (Yule) for each prior tree.

BMC Evolutionary Biology

Expert writing Tips

Best practice

When using "use a uniform average for", ensure that a uniform average is appropriate for your data. Consider whether applying the same average across all data points accurately reflects the underlying distribution or if weighted averages or other statistical methods might be more suitable.

Common error

Avoid using a uniform average when the data exhibits significant variability or distinct subgroups. Applying a uniform average in such cases can obscure important patterns and lead to misleading conclusions. Always assess the homogeneity of your data before opting for a uniform average.

Linguistic Context

The phrase "use a uniform average for" functions as a directive or instruction, advising the application of a consistent averaging method. Ludwig AI indicates that the phrase is grammatically correct but has limited real-world usage.

Expression frequency: Missing

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Ludwig's WRAP-UP

In summary, the phrase "use a uniform average for" is grammatically correct, but Ludwig AI shows it lacks extensive real-world examples. It functions as a directive to apply a consistent average, suitable for professional and scientific contexts. Since the phrase suggests an equal weighting of data points, it's most appropriate when the data is relatively homogeneous; otherwise, alternative methods like weighted averages should be considered. Related phrases include "apply a consistent mean to" and "employ a standard average for". Consider this guidance when you use a uniform average for your analysis.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

apply a consistent mean to

This alternative replaces "uniform average" with "consistent mean", emphasizing the application of a central tendency value that remains unchanged.

employ a standard average for

The term "standard average" is used instead of "uniform average", suggesting a generally accepted or typical averaging method.

utilize a constant average across

Using "constant average" instead of "uniform average" highlights the unchanging nature of the average being applied.

adopt a fixed average in

The phrase "fixed average" is used to indicate that the average value remains the same throughout the process.

implement a homogeneous average on

"Homogeneous average" is used in place of "uniform average", suggesting an even or consistent average applied across the dataset.

leverage a standardized mean for

This alternative uses "standardized mean" to convey the use of a mean calculated and applied according to a specific standard or protocol.

administer a regular average over

Replacing "uniform" with "regular" suggests that the averaging process is conducted in a consistent, methodical manner.

exercise a stable average within

This alternative highlights the stability of the applied average, indicating it does not fluctuate during the calculation.

make use of a consistent central value for

This alternative broadens the description by mentioning "central value" which may include mean, median or mode.

opt for a unvarying average in

The phrase "unvarying average" underscores the constant nature of the average used, emphasizing that it does not change over the course of the analysis.

FAQs

How can I appropriately "use a uniform average for" data analysis?

Ensure your data is relatively homogenous. If the data has high variability or distinct subgroups, consider whether a uniform average accurately represents the data, or if other methods like weighted averages are more appropriate.

What are the alternatives to "use a uniform average for" in statistical calculations?

Alternatives include "apply a consistent mean to", "employ a standard average for", or "utilize a constant average across", depending on the specific nuance you wish to convey.

When is it inappropriate to "use a uniform average for" data sets?

It is inappropriate when the data displays significant variability, outliers, or distinct subgroups. In such cases, measures like weighted averages, medians, or mode may provide a more accurate representation.

What does "use a uniform average for" imply about the underlying data?

It suggests that all data points are being treated equally in the averaging process, with no specific weighting or adjustment for individual values. This assumes that each data point contributes equally to the overall average.