lack of representativeness

USAGE SUMMARY

The phrase "lack of representativeness" is correct and usable in written English.
It is used to describe a situation where a sample of people does not accurately represent the population as a whole. For example: "The results of the survey were skewed due to the lack of representativeness of the sample group."

✓ Grammatically correct

Science

Encyclopedias

Academia

Human-verified examples from authoritative sources

Exact Expressions

59 human-written examples

Some of these registries, however, suffer from a relative lack of representativeness, while others are highly representative but cannot collect extensive clinical data.

Heart

Limitations of telephone surveys include lack of representativeness, as households with no landline telephone are not represented.

BMC Public Health

This lack of representativeness of our sample, although such sample were large and representative of a hospital's population, is a limitation that needs to be addressed in further population-level surveys.

BMC Musculoskeletal Disorders

Another factor that tends to limit their effectiveness is their perceived lack of representativeness.

Encyclopedia Britannica

We've got all the constraints of a two-party system and its comparative lack of representativeness compared to a multiparty parliamentary system.

Harvard University

The poor significance of the available haemostatic, coagulation and/or fibrinolytic parameters is probably due to their lack of representativeness, since haemostatic, coagulation and fibrinolytic systems are all involved in the thrombotic response (and some in atherogenesis itself).

Thérapie

Empirical evidence for the maintainability of object-oriented systems is far from conclusive, partly due to the lack of representativeness of the subjects and systems used in earlier studies.

Journal of Systems and Software

Regarding the school's low response rate of about 13% suggest a lack of representativeness.

Psicologia: Reflexão e Crítica

The lack of representativeness of the subject programs may pose a threat to external validity.

Journal of the Brazilian Computer Society

In this paper we conduct such an analysis for the CSWL waves for 2005 2013 and confirm that there is a lack of representativeness in most years.

SERIEs

Human-verified similar examples from authoritative sources

Similar Expressions

1 human-written examples

For methodological reasons (sample size and lack of statistical representativeness), it is difficult to take these dimensions into account in the qualitative survey.

European Transport Research Review

Expert writing Tips

Best practice

When discussing research limitations, explicitly state how the "lack of representativeness" might affect the generalizability of your findings. This demonstrates a critical understanding of your study's scope.

Common error

Don't assume your sample is representative simply because it's large. Always validate representativeness by comparing key demographics of your sample to those of the target population.

Linguistic Context

The phrase "lack of representativeness" functions primarily as a noun phrase. It describes a deficiency or absence of the quality of being representative, often referring to a sample or data set's failure to accurately reflect a larger population. Ludwig AI shows numerous examples in scientific and academic contexts.

Expression frequency: Very common

Frequent in

Science

80%

Academia

10%

Encyclopedias

5%

Less common in

Formal & Business

2%

News & Media

2%

Social Media

1%

Ludwig's WRAP-UP

The phrase "lack of representativeness" is a commonly used and grammatically sound term, predominantly found in scientific and academic literature. Ludwig AI confirms its appropriate usage for describing scenarios where a sample fails to accurately reflect a larger population. It's crucial to acknowledge this limitation in research to avoid overgeneralization. Related phrases include "non-representative sample" and "biased sample". While the phrase is valuable for technical accuracy, ensure to validate your sample’s representativeness before drawing conclusions. A potential oversight would be presuming representativeness without empirical backing. Overall, "lack of representativeness" serves as a critical reminder of the importance of proper sampling techniques and cautious interpretation of data.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

non-representative sample

Focuses on the characteristic of the sample itself, highlighting its failure to represent the population.

unrepresentative data

Emphasizes the data's failure to provide an accurate reflection of the overall situation.

biased sample

Highlights the presence of bias leading to the lack of accurate representation.

skewed representation

Indicates that the representation is distorted or unbalanced.

inadequate representation

Suggests that the representation is insufficient or incomplete.

limited representativeness

Indicates the extent of representation is restricted or not comprehensive.

deficient representation

Focuses on the shortcomings of the representation.

incomplete representation

Highlights that certain aspects are missing in the representation.

partial representation

Emphasizes that only a portion of the whole is represented.

non-inclusive sample

Points out the exclusion of certain groups, which affects overall representativeness.

FAQs

How does "lack of representativeness" affect research outcomes?

A "lack of representativeness" in a study sample can lead to skewed results that may not accurately reflect the broader population, limiting the generalizability of the findings. It's crucial to acknowledge and address this limitation when interpreting and applying research outcomes.

What are common causes of "lack of representativeness" in surveys?

Common causes include sampling bias (e.g., only surveying people who are easily accessible), low response rates, and using outdated contact information. Ensuring a random and diverse sampling method can help mitigate this issue.

How can I improve the representativeness of my sample?

Strategies for improving representativeness include using stratified sampling to ensure proportional representation of different subgroups, increasing sample size, and employing techniques to minimize non-response bias. Weighting the data based on known population characteristics can also help correct for a "lack of representativeness".

What are some alternatives to "lack of representativeness"?

You can use alternatives like "non-representative sample", "biased sample", or "skewed representation depending on the context".