incomplete data sources

USAGE SUMMARY

The phrase "incomplete data sources" is correct and usable in written English.
It can be used when referring to data sources that lack necessary information or are not fully reliable. Example: "The analysis was hindered by incomplete data sources, making it difficult to draw accurate conclusions."

✓ Grammatically correct

Science

News & Media

Human-verified examples from authoritative sources

Exact Expressions

4 human-written examples

The Department of Defense's Cyber Crime Center will expand its Digital Forensics Challenge, a program it has run since 2006, to include high school and college participants, tasking them with problems like tracing digital intrusions and reconstructing incomplete data sources.

Forbes

The contests he promotes include the Air Force's Cyber Patriot competition, which has high school contestants fending off a "Red Team" of hackers attempting to steal their data, and the Department of Defense's Digital Forensics Challenge, in which teens and college students compete to trace digital intrusions and reconstruct incomplete data sources.

Forbes

First, using two-source capture-recapture, it seeks to estimate and describe the pedestrian crash mortality burden among wheelchair users by examining overlapping capture between two incomplete data sources.

BMJ Open

Despite studies conducted to address the contextual factors associated with CRC screening, the findings have been mixed as a result of variations in research design, conceptual frameworks, the use of incomplete data sources, and measurement issues.

F1000Research

Human-verified similar examples from authoritative sources

Similar Expressions

56 human-written examples

Another source of incomplete data source might be the decision to exclude information from reviews that focused on one specialty or one technical procedure in medicine only.

BMC Medical Education

47 These assumptions were necessary to simplify the model or to take account of incomplete data into literature sources.

ClinicoEconomics and Outcomes Research

Rikkers et al. claim that the Australian Paradox is based on incomplete data because the sources utilised did not incorporate estimates for imported processed foods.

BMC Public Health

In the case of incomplete data from the source patient files, the research technicians contacted the local investigator to obtain the missing information.

Heart

For countries lacking a primary data source or with incomplete data, we needed to use data from alternative sources.

Global Health Action

In summary, in addition to handling the large and fast data input, the research issues of heterogeneous data sources, incomplete data, and noisy data may also affect the performance of the data analysis.

Journal of Big Data

Xiang et al. investigate multi-source incomplete data for AD and introduce a unified feature learning model to handle block-wise missing data which achieves simultaneous feature-level and source-level selection [72].

Brain Informatics

Expert writing Tips

Best practice

When using "incomplete data sources", clearly state the limitations this imposes on your analysis or conclusions. This enhances transparency and credibility.

Common error

Avoid drawing definitive conclusions based solely on "incomplete data sources". Acknowledge the uncertainty and potential for bias in your findings.

Linguistic Context

The phrase "incomplete data sources" functions as a noun phrase, typically acting as the subject or object of a sentence. It identifies a category of data sources characterized by missing or deficient information, as seen in the Ludwig examples.

Expression frequency: Rare

Frequent in

Science

75%

News & Media

17%

Formal & Business

8%

Less common in

Social Media

0%

Wiki

0%

Encyclopedias

0%

Ludwig's WRAP-UP

In summary, "incomplete data sources" is a noun phrase used to describe data sources lacking necessary information. As Ludwig AI confirms, the phrase is grammatically correct and usable in written English. The phrase is most frequently used in scientific contexts and, to a lesser extent, in news and media. When using "incomplete data sources", it is crucial to acknowledge the limitations and potential biases they introduce. Alternatives like "partial data sources" or "insufficient data sources" can be used depending on the context. It's important to avoid overstating conclusions based on such data and to employ appropriate statistical methods when possible.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

partial data sources

Indicates data sources that contain only some of the required information, suggesting a degree of incompleteness.

fragmented data sources

Emphasizes the scattered and disjointed nature of the data, implying that the data is not whole or complete.

insufficient data sources

Highlights the lack of adequate data sources to draw comprehensive conclusions.

deficient data sources

Focuses on the lack of essential information within the data sources.

limited data sources

Suggests that the available data sources are restricted in scope or quantity, leading to potential incompleteness.

flawed data sources

Highlights errors that lead to "incomplete data sources".

unreliable data sources

Indicates that the trustworthiness of data leads to "incomplete data sources".

inaccurate data sources

Highlights inaccuracies within the data sources that lead to an "incomplete data sources".

patchy data sources

Evokes an image of data with gaps and missing pieces, similar to incompleteness.

sparse data sources

Suggests that the density of data within the sources is low, resulting in an incomplete picture.

FAQs

How can I address issues arising from "incomplete data sources"?

Employ statistical methods to handle missing data, such as imputation or sensitivity analysis. Also, consider gathering additional data to supplement the existing "limited data".

What are some strategies for mitigating the impact of "incomplete data sources"?

Triangulate your findings by using multiple data sources, even if some are "unreliable data sources". This can help validate your results and identify potential biases.

How does the use of "incomplete data sources" affect the reliability of research?

The use of "incomplete data sources" can reduce the reliability of research. Always acknowledge this limitation and discuss the potential impact on your conclusions. Consider exploring "alternative data sources".

What are some alternatives to using "incomplete data sources" in analysis?

If possible, prioritize data collection to obtain more complete datasets. If that's not feasible, explore statistical methods that are robust to missing data or use "proxy variables" to fill the gaps.