data are poor for

USAGE SUMMARY

The phrase "data are poor for" is correct and usable in written English.
It can be used when discussing the quality or reliability of data in relation to a specific subject or analysis. Example: "The data are poor for drawing any significant conclusions about the effectiveness of the new treatment."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

1 human-written examples

In general, the data are poor for haploidentical HSCT, due to the high morbidity and mortality associated with graft-versus-host disease (GVHD) and rejection.

Application of Clinical Genetics

Human-verified similar examples from authoritative sources

Similar Expressions

58 human-written examples

In countries with concentrated epidemics, comparisons of population survey prevalence to ANC surveillance by sex showed a greater difference in women (53% downward reduction) as compared to men (44% downward reduction), although agreement between population survey data and the adjusted ANC data was poor, and especially so for men (Supplemental Fig. 2a and b).

AIDS

NHI and QV matching was incomplete due to address data being poor quality or not suitable for matching.

BMC Public Health

NHI and QV matching was incomplete due to NHI address data being poor quality or not suitable for matching.

BMC Public Health

First, reporting of design elements and data was poor and inconsistent with widely recognized standards for animal studies (Kilkenny et al., 2010).

eLife

It adds that "DIAC's data is poor".

The Guardian

It is shown that the cubic equations provide an adequate representation of the data for the simpler fluids but are poor for the more complex ones (e.g. C2H4, C2H6).

Chemical Engineering Science

For the last category, Data Rejected (colored in grey), the required data were inadequate for analysis due to poor instrument practice, exhibited extremely poor S/N or contained indiscernible artefacts or impurities, etc.

Journal of Cheminformatics

The inference that topographic data resolution is poor for operational use is further supported by the fact that DTMs were the most produced ALS data output by forestry companies.

New Zealand Journal of Forestry Science

Performance of motif-based methods on both data sets was poor for all non- Drosophila target species (supplementary table S3, Supplementary Material online), further supporting our choice of k-mer-based methods for cross-species CRM discovery.

Genome Biology and Evolution

These are important factors to consider when selecting portion condemnation designations for syndromic surveillance; a previous study by Thomas et al. [ 19], investigating the use of portion condemnations in market hogs, noted that the quality of data recording was poor for organs that were not considered to be economically important or a concern for food safety.

BMC Veterinary Research

Expert writing Tips

Best practice

When using the phrase "data are poor for", clearly specify what the data is inadequate for. This adds clarity and context to your statement.

Common error

Avoid using "data are poor" without specifying the context or reason. Provide specific details about the limitations or inadequacies of the data.

Linguistic Context

The phrase "data are poor for" functions as an evaluative statement, indicating that the data in question is not of sufficient quality or quantity to support a specific purpose or analysis. As Ludwig AI explains, this means the available information is deficient.

Expression frequency: Common

Frequent in

Science

70%

News & Media

20%

Formal & Business

10%

Less common in

Encyclopedias

0%

Wiki

0%

Reference

0%

Ludwig's WRAP-UP

The phrase "data are poor for" is a grammatically sound expression used to indicate that data is insufficient or inadequate for a particular purpose. Ludwig AI validates this, and the phrase sees common usage in scientific, news, and formal contexts. When employing this phrase, be precise about why the data is lacking. Consider alternatives like "data are insufficient for" or "data are inadequate for" to fine-tune your meaning.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

data are insufficient for

Emphasizes a lack of enough data to support a conclusion.

data are inadequate for

Highlights that the data does not meet the required standard or purpose.

data are lacking for

Indicates an absence of data for a specific area or analysis.

data are unreliable for

Suggests the data cannot be trusted for a particular application.

data are unsuitable for

Conveys the data is not appropriate for a given purpose.

data are deficient for

Implies the data is incomplete or has shortcomings for a specific need.

data are weak for

Suggests the data provides limited support or evidence.

data are scarce for

Highlights the limited availability of data for a certain topic.

data are limited for

Emphasizes the restricted scope or extent of the data.

data are imperfect for

Indicates the data has flaws or inaccuracies for a particular analysis.

FAQs

What does it mean when I say "data are poor for" something?

Saying "data are poor for" something means that the available data is insufficient, unreliable, or inadequate to draw accurate conclusions or make informed decisions about that specific thing.

Are there synonyms for "data are poor for"?

Yes, you can use alternatives like "data are insufficient for", "data are inadequate for", or "data are lacking for" depending on the specific context.

In what contexts might I use the phrase "data are poor for"?

You might use this phrase in research papers, reports, or presentations when discussing the limitations of data used in an analysis or study. It's common in fields like science, statistics, and economics.

How can I improve the quality of data if "data are poor for" my needs?

Improving data quality involves strategies such as collecting more data, refining measurement methods, addressing biases, and validating data sources. If the "data are unreliable for" a specific purpose, consider using alternative data sets or methods.