thoroughness of data

USAGE SUMMARY

The phrase "thoroughness of data" is correct and usable in written English.
It can be used when discussing the completeness and detail of data in research, analysis, or reporting contexts. Example: "The thoroughness of data collected during the study was crucial for drawing accurate conclusions."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

2 human-written examples

However, if the primary purpose is performance/outcomes monitoring then timeliness is less important than accuracy and thoroughness of data capture.

BMC Infectious Diseases

Establishing the reliability of data also requires transparency and thoroughness of data reporting (Klimisch et al. 1997), which constitute "secondary validity" of the data.

Environmental Health Perspectives

Human-verified similar examples from authoritative sources

Similar Expressions

57 human-written examples

Even so, such databases introduce study biases with regard to the quality, validity and thoroughness of the data; accordingly, we selected those physicians whose records were considered most reliable in terms of quality.

Family Practice

Two secondary reviewers [MTC and MAC], who had not conducted the interviewers, independently reviewed separate random samples of 50% of the transcripts for accuracy and thoroughness of the data extraction and selection of themes, sub-themes, and sub-sub-themes.

BMC Medical Ethics

Two secondary reviewers, who had not conducted the interviewers, independently reviewed separate random samples of 50% of the transcripts for accuracy and thoroughness of the data extraction and selection of themes, sub-themes, and sub-sub-themes.

BMC Medical Ethics

I'd like to commend the authors on the thoroughness of their descriptions of data quality and sample quality - I found Figures  1, 2, 3 both useful and sensible in this regard - this adds to the value of the RNAseq data immeasurably, as it provides context often missing from similar studies.

Biology Direct

Data were collected by hospital administrators who may not have, for whatever reasons, the same rigour and thoroughness of researchers using the data for primary investigative purposes.

BMC Oral Health

This leads to variations in the care with which informed consent is obtained, diligence in application of inclusion and exclusion criteria, rigor of collecting information on concomitant medications and use of over-the-counter treatments, attention to timeframes of data collection, thoroughness of adverse event reporting, and completeness of data collection and recording [ 37].

Alzheimer's Research and Therapy

Thus, we gain no flexibility or thoroughness of documentation of the underlying data values by storing them vertically (unlike with LAGOSLIMNO).

GigaScience

The quality of data collected is tied to the thoroughness of comments made by reviewers, their subjectivity and their broader capacity of interpretation of the policy context.

Health Research Policy and Systems

Petraeus emphasized the thoroughness of today's review process, noting that the packets of data that are circulated to review-board members about Medal of Honor nominees are often as thick as phone books.

The New York Times - Magazine

Expert writing Tips

Best practice

When assessing research or reports, explicitly mention the "thoroughness of data" collection and analysis to emphasize the rigor and reliability of the findings.

Common error

Avoid assuming that a large dataset automatically equates to "thoroughness of data". Ensure that the data is not only abundant but also relevant, accurate, and properly contextualized.

Linguistic Context

The phrase "thoroughness of data" functions as a noun phrase, typically serving as the subject or object of a sentence. It describes the quality of data in terms of its completeness and detail, as supported by Ludwig AI.

Expression frequency: Common

Frequent in

Science

50%

News & Media

25%

Formal & Business

25%

Less common in

Social Media

0%

Wiki

0%

Encyclopedias

0%

Ludwig's WRAP-UP

In summary, "thoroughness of data" is a key factor for reliable research and informed decision-making. As indicated by Ludwig AI, this phrase is grammatically correct and commonly used in academic, scientific, and news contexts. When using this phrase, remember that true thoroughness requires not only data quantity but also relevance and accuracy. Alternatives like "data completeness" or "data comprehensiveness" may be used depending on the intended nuance. By prioritizing data quality and comprehensive analysis, you can ensure that your conclusions are well-supported and trustworthy.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

data completeness

This focuses specifically on whether all necessary data points are present.

data comprehensiveness

This emphasizes the extent to which the data covers all relevant aspects.

data integrity

This refers to the accuracy and consistency of the data over its lifecycle.

data depth

This highlights the level of detail and granularity within the data.

data exhaustiveness

This suggests that all possible data points have been considered and included.

data richness

This implies the data provides a wealth of information and insights.

breadth of data

It focuses on the range and variety of data included.

scope of data

This indicates the extent of the area or subject that the data covers.

detail of data

This is about the amount of specific information the data contains.

intensity of data

This stresses the depth and concentration of information within the data.

FAQs

How can I assess the "thoroughness of data" in a research study?

Consider the data collection methods, sample size, and whether all relevant variables were examined. Look for detailed documentation explaining how the data was gathered and analyzed to ensure "data completeness".

What does it mean for data to be considered "thorough"?

Data is thorough when it is comprehensive, detailed, and covers all relevant aspects of the subject matter. It ensures that no significant information is missing, and the analysis is based on a complete understanding of the available evidence. This ensures "data integrity".

What are some alternatives to "thoroughness of data"?

You can use alternatives like "data comprehensiveness", "data completeness", or "data depth" depending on the specific aspect you want to emphasize.

Why is the "thoroughness of data" important in data analysis?

It's crucial because it directly impacts the validity and reliability of the results. If data is incomplete or lacks detail, the analysis may be biased or misleading, leading to incorrect conclusions. So you should aim for the best "scope of data" and "detail of data".