cautious data

USAGE SUMMARY

The phrase "cautious data" is not a standard expression in written English, but it can be understood in context.
You can use it when referring to data that has been collected or presented with care, possibly to avoid misinterpretation or misuse. Example: "The researchers provided cautious data to ensure that their findings would not be misrepresented in the media."

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

1 human-written examples

The key to overcome the issues with different samples and analysis is vigilance in sample preparation, state of the art mass spectrometry, careful data processing and cautious data analysis.

Human Reproduction

Human-verified similar examples from authoritative sources

Similar Expressions

59 human-written examples

The cautious, data-driven economists at Germany's central bank would not have made that statement without studying the issue thoroughly.

The New York Times

One must therefore be cautious interpreting data from this study, as the Bland and Altman analyses and the concordance analyses may use reference data that have a wider spread than usual and thus wider acceptance criteria [ 3, 4].

Critical Care

The three larger networks have for the most part been cautious, keeping data use at bay with the usual mixture of high prices and complicated tariffs.

The Guardian - Tech

Despite critics warning that the Fed's policies to keep interest rates low would stoke asset bubbles and inflation, Yellen took a cautious and data-driven approach to withdrawing the stimulus.

Los Angeles Times

Unfortunately, one must always be cautious about the data.

The Economist

It is difficult to judge whether the agency has actually become more cautious, because the data on which it bases decisions are usually not publicly released, and the agency does not discuss drugs under review.

The New York Times

Even if a company doesn't want to look at your data, "cautious lawyers are going to reserve some rights, so if something happens, they're not going to get sued".

The New Yorker

Dr. Martin D. Abeloff, a member of the President's Cancer Advisory Board and clinical director of the oncology center at Johns Hopkins University, said, "We have to be very cautious" about releasing data early.

The New York Times - Science

But one may beg to differ with him on some things, and especially on the conclusions he draws (or invites his readers to draw).First, one must be cautious about the data.

The Economist

Whether or not that's true, Europeans certainly are more cautious with their data than Americans.

Forbes

Expert writing Tips

Best practice

When presenting "cautious data", clearly state the limitations and potential biases to avoid misinterpretations. This ensures transparency and responsible data usage.

Common error

Avoid drawing definitive conclusions from "cautious data" without acknowledging the uncertainties and limitations. Always temper your findings with appropriate qualifiers.

Linguistic Context

The phrase "cautious data" functions as an adjective-noun combination. The adjective "cautious" modifies the noun "data", indicating that the data requires careful handling, interpretation, or analysis. Ludwig AI highlights its usage in contexts requiring vigilance in data processing and analysis.

Expression frequency: Rare

Frequent in

Science

33%

News & Media

33%

Formal & Business

33%

Less common in

Encyclopedias

0%

Wiki

0%

Reference

0%

Ludwig's WRAP-UP

The phrase "cautious data" signifies that the data should be handled with care and interpreted thoughtfully, acknowledging its limitations. Ludwig AI indicates the phrase is grammatically acceptable but infrequent, finding instances across science, news, and business domains. When using "cautious data", it's best practice to clearly articulate any limitations or biases to promote responsible usage and prevent misinterpretations. Alternatives include "carefully analyzed data" or "data requiring careful interpretation", depending on the context. To avoid errors, refrain from overstating conclusions without acknowledging uncertainties.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

carefully analyzed data

Emphasizes the thoroughness and attention to detail in the analysis process.

data requiring careful interpretation

Highlights the need for thoughtful and nuanced understanding of the information.

prudent data handling

Focuses on the responsible and judicious management of information.

data with caveats

Indicates that the data comes with specific limitations or conditions that must be considered.

data needing validation

Suggests the data requires verification to confirm its accuracy and reliability.

guarded data release

Highlights a carefully controlled and restricted distribution of data.

verified and validated data

Emphasizes that data underwent verification and validation.

data treated with scrutiny

Indicates that the data has been examined closely and critically.

data requiring circumspect analysis

Underscores that the analysis needs to be careful and well-considered.

data under strict control

Highlights that data is managed under highly regulated environments.

FAQs

How can I use "cautious data" responsibly?

Use "cautious data" responsibly by clearly stating any limitations, potential biases, and uncertainties associated with the data. Transparency ensures that others can interpret the data accurately.

What does it mean to interpret data cautiously?

To interpret data cautiously means to avoid drawing firm conclusions without considering potential limitations, biases, or confounding factors. It involves acknowledging the uncertainties inherent in the data.

Which phrases are similar to "cautious data"?

Alternatives to "cautious data" include "carefully analyzed data", "data requiring careful interpretation", and "prudent data handling", depending on the specific nuance you want to convey.

When should I use the phrase "cautious data"?

Use "cautious data" when you want to emphasize that the data should be handled and interpreted with care, recognizing its potential limitations or sensitivities. This is especially important in scientific or analytical contexts where precision is crucial.