biased sample

USAGE SUMMARY

The phrase "biased sample" is correct and usable in written English.
It is typically used in statistics and research to refer to a sample that does not accurately represent the population from which it is drawn, leading to skewed results. Example: "The study's findings were questionable due to the use of a biased sample that favored one demographic over others."

✓ Grammatically correct

Science

News & Media

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

While compelling, these interviews may represent a biased sample.

The New York Times - Health

And if "Dutch women don't get depressed", I must be meeting a very biased sample.

The Economist

Not all of the casual-sex experiences recorded on the site were positive, even among what is surely a heavily biased sample.

The New Yorker

After the election, more irregularities were discovered, among them spoiled ballots, voting-machine errors, provisional ballots mistakenly invalidated, and biased sample recounts.

The New Yorker

But I noticed two things that seem significant to me: 1) most of the people who ask that question didn't play football themselves, so it's kind of a biased sample.

The New Yorker

Because those users following @twitstat are likely to be "hardcore" users (given that they care about things like retweet counts), it's a heavily biased sample.

TechCrunch

But what was recorded by the monks or discovered by the archeologists must be regarded as a biased sample.

Rice

This approach was used to simulate a spatially biased sample by selecting stems based on their proximity to random points around the boundary of the stand.

New Zealand Journal of Forestry Science

GBIF data for Legumes are a geographically biased sample.

Plosone

The studied S group, including almost 50% of the women recorded after a symphysiotomy, might be a biased sample.

Plosone

Based on our criteria, we may obtain a biased sample of the NG2 cell population and failed to identify NG2 cells in discrete states of differentiation.

Plosone

Expert writing Tips

Best practice

When discussing research, explicitly acknowledge the limitations introduced by a "biased sample" and explain how this bias might affect the interpretation of results.

Common error

Avoid generalizing findings from a "biased sample" to the entire population. Be cautious about drawing broad conclusions without acknowledging the sample's limitations.

Linguistic Context

The phrase "biased sample" functions as a noun phrase, where "biased" acts as an adjective modifying the noun "sample". It typically describes a selection or subset that does not accurately represent the larger population from which it was drawn. As stated by Ludwig, it is commonly used in research and statistical contexts.

Expression frequency: Very common

Frequent in

Science

55%

News & Media

40%

Formal & Business

5%

Less common in

Wiki

0%

Encyclopedias

0%

Reference

0%

Ludwig's WRAP-UP

In summary, "biased sample" refers to a non-representative subset of a population, frequently used in research and statistics to denote flawed data collection. Ludwig AI confirms its grammatical correctness and highlights its prevalence in science and news contexts. When using this phrase, acknowledge the limitations and avoid overgeneralization. Related phrases like "skewed sample" or "unrepresentative sample" offer similar meanings. Understanding and addressing potential biases is crucial for accurate data interpretation.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

skewed sample

Emphasizes the distorted representation of the population.

unrepresentative sample

Directly points out the lack of representativeness.

non-random sample

Highlights the lack of randomness in the selection process.

selective sample

Suggests that the sample was chosen based on specific criteria, potentially introducing bias.

distorted subset

Focuses on the warped or misrepresented nature of the sample as part of a larger set.

self-selected sample

Refers to a sample where participants volunteer, potentially skewing the results.

convenience sample

Indicates that the sample was chosen based on ease of access rather than representativeness.

cherry-picked sample

Implies a deliberate selection of favorable data, leading to a biased outcome.

prejudiced selection

Highlights the element of prejudice or preconceived notions influencing the sample selection.

unbalanced representation

Highlights the unequal proportions of different elements within the sample.

FAQs

How can I identify if a sample is a "biased sample"?

A "biased sample" typically arises when the sampling method systematically favors certain individuals or groups over others. Look for non-random selection processes or characteristics of the sample that don't align with the broader population.

What are the consequences of using a "biased sample" in research?

Using a "biased sample" can lead to inaccurate conclusions and flawed generalizations about the population. It can skew results, misrepresent trends, and compromise the validity of research findings. Consider using an "unbiased sample" if possible.

What can I say instead of "biased sample"?

You can use alternatives like "skewed sample", "unrepresentative sample", or "non-random sample" depending on the context.

How does a "biased sample" differ from a random sample?

A "biased sample" systematically favors certain outcomes, while a random sample gives every member of the population an equal chance of being selected, aiming for an unbiased representation. Therefore, random samples are less prone to skewing results. Consider using an "unbiased sample" when performing research.