due to data insensitivity

USAGE SUMMARY

The phrase "due to data insensitivity" is correct and usable in written English.
It can be used in contexts where you are explaining a situation or outcome that arises because of a lack of sensitivity or responsiveness to data. Example: "The results of the experiment were inconclusive, due to data insensitivity in the measurement tools used."

✓ Grammatically correct

Science

News & Media

Human-verified examples from authoritative sources

Exact Expressions

1 human-written examples

Of the 34 non-significant effects, 73.5% were due to data insensitivity.

Psychoneuroendocrinology

Human-verified similar examples from authoritative sources

Similar Expressions

59 human-written examples

"Due to data limitations..

Los Angeles Times

The second scenario was used to simulate the hypothesis that satellite data cannot capture the full range of variance of forest structure due to the insensitivity of satellite measurements to vertical vegetation structure.

Carbon Balance and Management

However, clinically useful normative data for estradiol secretion in boys has not previously been established due to the insensitivity of current methods used in clinical routine.

BMC Endocrine Disorders

RF are easy to handle due to their insensitivity to interior room light.

Physica Medica

The transmissibility based operational modal analysis (TOMA) has drawn great attention due to its insensitivity to the nature of external excitation.

Engineering Structures

Due to the insensitivity of the sensing properties to the immobilization matrix, this material can be easily incorporated in the most appropriate matrix depending on the application.

Sensors and Actuators A: Physical

To evaluate the safety and feasibility of enhancement balloon vaginoplasty (EBV) in cases with blind vagina due to androgen insensitivity syndrome.

Fertility and Sterility

Due to the insensitivity of rapid tests for respiratory viruses, nucleic acid amplification tests are quickly becoming the standard of care.

Journal of Clinical Virology

Reaven discusses what led him to his experiments that proved type II diabetes was due to insulin insensitivity, as opposed to lack of insulin in the blood, and how his research progressed.

Stanford University

This could be due to the insensitivity of SCS to low rainfall depths.

Applied Water Science

Expert writing Tips

Best practice

When using "due to data insensitivity", ensure you clearly specify what kind of data and which measurement or analysis is affected. This provides context and clarity for the reader.

Common error

Avoid using "due to data insensitivity" as a vague explanation. Instead, identify the specific properties of the data or methods that lead to the insensitivity, such as sample size, scale or instruments used.

Linguistic Context

The phrase "due to data insensitivity" functions as a causal connector, indicating that a particular outcome or result is a consequence of the data's inability to capture subtle variations. Ludwig AI confirms its usability in explaining situations arising from a lack of sensitivity to data.

Expression frequency: Rare

Frequent in

Science

75%

News & Media

13%

Formal & Business

0%

Less common in

Academia

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "due to data insensitivity" is a causal connector used to explain outcomes resulting from a lack of responsiveness to data. As highlighted by Ludwig AI, it's a usable phrase in English, particularly in scientific and technical contexts. While grammatically correct, it's relatively rare. For clarity, specify the data type and affected analysis. Alternatives include "resulting from data limitations" or "caused by inadequate data resolution". The phrase is most frequently found in scientific sources.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

resulting from data unresponsiveness

Replaces "insensitivity" with "unresponsiveness", emphasizing a lack of reaction from the data.

arising from data limitations

Shifts the focus to "limitations" rather than "insensitivity", highlighting constraints in the data itself.

caused by inadequate data resolution

Specifies "inadequate data resolution" as the cause, pinpointing a lack of clarity or detail in the data.

attributable to data's lack of precision

Emphasizes a lack of accuracy with the term "lack of precision" as the cause.

stemming from deficient data granularity

Focuses on "deficient data granularity", referring to the level of detail available.

consequent to data's coarse nature

Highlights the "coarse nature" of the data, suggesting a lack of refinement.

owing to data's obtuse characteristics

Uses "obtuse characteristics" to denote data that is difficult to interpret effectively.

because of data's unrefined state

Attributes the cause to the "unrefined state" of the data, indicating a need for further processing.

as a result of data's inherent bias

Highlights potential distortions in the data using "inherent bias" as the cause.

linked to data's restricted scope

Focuses on "restricted scope", indicating a limited range or breadth of the data.

FAQs

How can I use "due to data insensitivity" in a sentence?

Use "due to data insensitivity" to explain why certain results were not significant or why a particular analysis was limited. For example, "The study's findings were inconclusive "due to data insensitivity" in detecting subtle changes."

What are some alternatives to "due to data insensitivity"?

Alternatives include "resulting from data limitations", "caused by inadequate data resolution", or "attributable to data's lack of precision", depending on the specific context.

Is it better to say "because of data insensitivity" or "due to data insensitivity"?

Both phrases are grammatically correct, but ""due to data insensitivity"" is often perceived as more formal. "Because of data insensitivity" is equally acceptable and commonly used.

What does "data insensitivity" actually mean?

"Data insensitivity" refers to the inability of a measurement, method, or analysis to detect subtle changes or variations in the data, leading to a lack of responsiveness to underlying patterns or effects.