unrepresentative data

USAGE SUMMARY

The phrase "unrepresentative data" is correct and usable in written English.
It can be used when discussing data that does not accurately reflect the population or phenomenon being studied. Example: "The conclusions drawn from the unrepresentative data may lead to misleading results in the research."

✓ Grammatically correct

Science

News & Media

Academia

Human-verified examples from authoritative sources

Exact Expressions

7 human-written examples

Unrepresentative data samples are likely to reduce the utility of data classifiers in practical application.

Expert Systems with Applications

With so much data already in by that time, unrepresentative data at the end of a night can be a big surprise.

The New York Times

And the authors reckon the Reinhart-Rogoff method of calculating average growth gave outsize weight to unrepresentative data points (including one year of abysmal New Zealand data).

The Economist

The Planning Commission evaluation found that official statistics on nutrition generated by the concerned departments "do not represent grassroots reality" and linked the "unreliable and unrepresentative" data to the misuse of available funds in the Integrated Child Development Scheme.

The New York Times

In addition to the poverty of ethics arising from the failure to gain informed consent and the lack of accountability of sponsoring companies, it is highly unlikely in any scientific sense that unrepresentative data from algorithmic profiling can establish causality and predictability.

The Guardian - Tech

However, during manipulation of images a positive relationship between the original data and the resulting electronic image must be maintained to avoid the presentation of unrepresentative data as well as the loss of meaningful signals.

EMBO Molecular Medicine

Human-verified similar examples from authoritative sources

Similar Expressions

53 human-written examples

As important, we found that the distribution of studies was unrepresentative, the data analyzed less than ideal, and the specific criteria for determining success frequently unclear.

Agricultural Water Management

Artificial laboratory conditions and constraints imposed by the direct measurement systems, such as the small measuring area of a force plate, can have a strong influence on human ability to bounce and jump, naturally yielding unrepresentative force data.

Journal of Sound and Vibration

Due to the possibly varying number of recorded mappings and consequently different patterns for different services, there is some uncertainty regarding the reliability of predictions across the service base caused by possibly insufficient and unrepresentative log data.

Journal of Cloud Computing

A flawed analysis of unrepresentative state achievement data.

Stanford University

However, it is not generally influenced by extreme values (outliers), and as a result it is particularly useful in situations where there are unusually low or high values that would render the mean unrepresentative of the data.

Critical Care

Expert writing Tips

Best practice

When using "unrepresentative data", clarify why the data is unrepresentative and how it might affect your analysis. Be specific about the potential biases or limitations.

Common error

Avoid drawing broad conclusions from "unrepresentative data". Acknowledge the limitations and specify the population or context to which the findings are applicable.

Linguistic Context

The phrase "unrepresentative data" functions as an adjectival phrase modifying the noun "data". It describes data that does not accurately reflect the larger population or phenomenon being studied. Ludwig confirms its usability in diverse contexts.

Expression frequency: Uncommon

Frequent in

Science

50%

News & Media

35%

Academia

15%

Less common in

Formal & Business

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

The phrase "unrepresentative data" aptly describes data that fails to accurately mirror a larger population or phenomenon. According to Ludwig, the phrase is grammatically sound and used in various contexts. Common contexts include science, news & media, and academia. When using this term, it is advisable to specify why the data is unrepresentative and avoid drawing broad conclusions based solely on such data. Alternatives like "biased data" or "non-representative data" can be used depending on the nuance you want to convey. It is crucial to recognize the limitations and potential biases associated with this type of data to make informed decisions.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

non-representative data

A more formal way of stating that the data does not accurately reflect the population.

non-valid data

Formally indicates that the data does not meet the criteria for validity.

biased data

Emphasizes the presence of systematic error or prejudice in the data.

skewed data

Highlights the distortion or imbalance in the data distribution.

distorted data

Highlights the alteration or misrepresentation of the original data.

flawed data

Focuses on the imperfections or defects in the data collection or processing.

misleading data

Suggests that the data could lead to incorrect conclusions or interpretations.

inaccurate data

Highlights the lack of correctness or precision in the data.

unreliable data

Emphasizes the untrustworthiness or inconsistency of the data.

incomplete data

Indicates that the data is missing key elements or observations.

FAQs

What does "unrepresentative data" mean?

"Unrepresentative data" refers to a set of data that does not accurately reflect the characteristics of the larger population or phenomenon it is meant to describe. This can lead to skewed results and inaccurate conclusions.

How does "biased data" differ from "unrepresentative data"?

While both terms indicate problems with data quality, "unrepresentative data" simply means the sample doesn't mirror the population. "Biased data", on the other hand, implies a systematic error that skews the data in a specific direction.

What are the consequences of using "unrepresentative data"?

Using "unrepresentative data" can lead to flawed analyses, incorrect predictions, and ineffective decision-making. It's crucial to identify and address any potential biases or limitations in the data.

What are some alternatives to saying "unrepresentative data"?

Depending on the context, you could use terms like "skewed data", "biased data", "flawed data", or "non-representative data".