unsatisfactory data

USAGE SUMMARY

The phrase "unsatisfactory data" is correct and usable in written English.
It can be used when referring to data that does not meet the required standards or expectations for a particular analysis or decision-making process. Example: "The results of the experiment were based on unsatisfactory data, leading to inconclusive findings."

✓ Grammatically correct

Science

News & Media

Human-verified examples from authoritative sources

Exact Expressions

3 human-written examples

More unsatisfactory data is likely to intensify pressures on the Obama administration to mount a more muscular effort to stem foreclosures beyond the Treasury's campaign this week.

The New York Times

Of the 506 patients recruited, eight were excluded because of unsatisfactory data collection, and 20 patients withdrew their consent during the period of data collection, for a total of 478 patients for whom data were available for the present analysis.

Breast Cancer Research

Two other methods of RNA extraction were evaluated (Qiagen Plant RNA easy kit and Trizol), but the yields and DNA purity in our hands were unsatisfactory (data not shown).

BMC Plant Biology

Human-verified similar examples from authoritative sources

Similar Expressions

57 human-written examples

Preliminary RT-qPCR trials on DEGs with moderate RPKM showed unsatisfactory amplification (data not shown).

BMC Genomics

Williams and Hardy said this approach was unsatisfactory because telecommunications data could reveal significant private details about an individual.

The Guardian

These specimens, which had high average plate CT values were excluded from the final study analysis due to unsatisfactory RT-PCR data.

BMC Genomics

The 50 participants who attempted home testing with technically unsatisfactory or no data on one or both systems are shown in table 2. They differed little in their demographics from those who were successful.

BMJ Open

Samples with incomplete data, unsatisfactory biopsies, and biopsies with ambiguous diagnoses or non-specific labeling of location of origin (e.g., "close to 6 o'clock", "between 2 and 3 o'clock") were excluded.

BMC Cancer

The remaining 40% unmapped reads could be ascribed to the following reasons: (1) some genetic polymorphisms may occur in the E. granulosus genome which interferes with Bowtie mapping; (2) unsatisfactory available genome data; some sequences are probably absent in the current draft genome of E. granulosus [ 16]; (3) miRNAs sequencing errors.

BMC Genomics

However, the results were unsatisfactory and effective data-mining techniques that apply appropriate comprehensive datasets are needed.

BMC Systems Biology

The sensitivity and specificity for the studies data (included unsatisfactory samples) and underestimation rate of unsatisfactory samples were also calculated.

BMC Cancer

Expert writing Tips

Best practice

When reporting research results, be specific about why the data is considered "unsatisfactory". Provide details on the specific issues (e.g., missing values, biases, measurement errors) to give readers a clear understanding of the data's limitations.

Common error

Avoid using "unsatisfactory data" as a vague dismissal. Instead, pinpoint the exact reasons for the data's inadequacy. For example, instead of saying "the data was unsatisfactory", specify: "the data was unsatisfactory due to a high percentage of missing values and potential selection bias".

Linguistic Context

The phrase "unsatisfactory data" functions as a noun phrase where the adjective "unsatisfactory" modifies the noun "data". It describes data that does not meet the required standards or expectations. Ludwig AI confirms its grammatical correctness.

Expression frequency: Uncommon

Frequent in

Science

75%

News & Media

25%

Formal & Business

0%

Less common in

Encyclopedias

0%

Wiki

0%

Reference

0%

Ludwig's WRAP-UP

The phrase "unsatisfactory data" is a grammatically sound and professionally acceptable term used to describe data that fails to meet specific requirements or standards. As confirmed by Ludwig AI, it commonly appears in scientific and news contexts, signifying limitations or flaws within datasets. When using the term, it's crucial to specify the reasons for the data's inadequacy. Alternatives like "inadequate data" or "poor quality data" can be used depending on the specific context.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

inadequate data

Replaces "unsatisfactory" with "inadequate", focusing on the insufficiency of the data.

insufficient data

Similar to "inadequate data", this phrase highlights the lack of enough data.

poor quality data

Focuses on the quality of the data, rather than its ability to satisfy requirements.

unreliable data

Emphasizes the trustworthiness of the data as the primary concern.

flawed data

Highlights the presence of errors or defects in the data.

deficient data

Similar to "inadequate", but may imply a more fundamental lack.

substandard data

Indicates that the data fails to meet a required level of quality.

compromised data

Suggests that the data has been corrupted or tampered with.

tainted data

Implies that the data has been negatively affected by some external factor.

invalid data

Indicates that the data is not valid or accurate for its intended purpose.

FAQs

How can I use "unsatisfactory data" in a sentence?

You can use "unsatisfactory data" to describe data that is not adequate or reliable for a particular purpose. For example: "The conclusions were based on "unsatisfactory data" and should be interpreted with caution."

What are some alternatives to "unsatisfactory data"?

Some alternatives include "inadequate data", "poor quality data", or "unreliable data". The best choice depends on the specific reason the data is considered unsatisfactory.

Is it better to say "unsatisfactory data" or "incomplete data"?

Whether to use "unsatisfactory data" or "incomplete data" depends on the context. "Incomplete data" refers specifically to missing information, while "unsatisfactory data" is a broader term that can refer to data that is flawed, biased, or otherwise unsuitable, even if it is technically complete.

How does "unsatisfactory data" affect research conclusions?

Using "unsatisfactory data" can lead to unreliable or invalid research conclusions. It's important to acknowledge and address the limitations of the data when interpreting results. Depending on the degree of impact, you may want to consider using alternatives like "supplementary data" to reach reliable results.