grouped data

USAGE SUMMARY

The phrase "grouped data" is correct and usable in written English.
It is typically used in statistical or data analysis contexts to refer to data that has been organized into groups for easier analysis or interpretation. Example: "The results of the survey were presented as grouped data, allowing us to see trends across different demographics."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

All grouped data are presented as mean ± SEM.

Protein & Cell

Table 1 summarizes the importance of grouped data.

SERIEs

We used traditional grouped data analysis (ANOVA) as well as a more novel single-subject analysis.

Journal of Biomechanics

We refer to the grouped data as the "amplitude ratio gather".

Earth, Planets and Space

First, it gives explicit treatment to these grouped data in standard gravity regressions.

SERIEs

Such test cannot be implemented here because of the grouped data.

SERIEs

I handle these grouped data in a raw manner in the estimation.

SERIEs

Mapping and interpretation was used to identify patterns, contradictions and respondent clusters in thematically grouped data.

Pastoralism

It caches the static data on each Mapper local disk, and caches the grouped data on each Reducer local disk.

Journal of Big Data

Section 3 introduces the econometric model and explains the implications of grouped data in terms of identification of fixed effects.

SERIEs

A potential limitation of working with grouped data is in the identification of fixed effects in the estimation of Eqs.

SERIEs

Expert writing Tips

Best practice

When presenting "grouped data", clearly define the criteria used for grouping to ensure transparency and replicability.

Common error

Avoid drawing individual-level conclusions from "grouped data"; ecological fallacy can occur when group trends are assumed to apply to all individuals within those groups.

Linguistic Context

The phrase "grouped data" functions primarily as a noun phrase. It is used to identify and refer to data that has been organized into groups or categories. This is supported by Ludwig's examples, which showcase its use in contexts like statistical analysis and data presentation.

Expression frequency: Very common

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Encyclopedias

0%

Ludwig's WRAP-UP

The phrase "grouped data" is a grammatically correct and frequently used noun phrase, predominantly in scientific and statistical contexts. According to Ludwig, it describes data that has been organized into categories for analysis or presentation. The key takeaway is that while "grouped data" simplifies analysis, it's essential to be cautious about drawing individual-level inferences from it. Alternatives include "aggregated data" and "categorized data", each emphasizing slightly different aspects of data handling.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

Aggregated data

Focuses on the process of combining data from multiple sources into a single summary.

Categorized data

Emphasizes the act of sorting data into distinct categories based on shared attributes.

Binned data

Specifically refers to data that has been sorted into discrete bins or intervals.

Segmented data

Highlights the division of data into meaningful segments for targeted analysis.

Clustered data

Refers to data points that have been grouped based on similarity, often using algorithms.

Pooled data

Indicates the combining of data from different sources or time periods to increase statistical power.

Summarized data

Emphasizes the presentation of data in a concise, overview format.

Classified data

Stresses the arrangement of data according to predefined classes or types.

Tabulated data

Focuses on presenting data in a structured table format for easy comparison.

Consolidated data

Highlights the process of bringing together data from various sources into a unified whole.

FAQs

How is "grouped data" used in statistical analysis?

"Grouped data" is often used in statistical analysis to summarize and analyze large datasets. It involves organizing data into categories or intervals, allowing for easier identification of trends and patterns. Techniques like histograms, frequency distributions, and contingency tables are commonly employed to analyze "categorized data".

What are the advantages of using "grouped data"?

Using "grouped data" simplifies complex datasets, making them easier to understand and analyze. It reduces the computational burden, highlights key trends, and facilitates comparisons between different groups. However, it's important to note that grouping can also lead to a loss of detail and potential bias.

How does "grouped data" differ from raw data?

Raw data consists of individual, unorganized data points, while "grouped data" involves organizing these points into categories or intervals. Grouping provides a summarized view, sacrificing some detail for the sake of clarity and analytical efficiency. For example, instead of individual ages, you might have age groups like 20-30, 31-40, and so on.

What statistical methods are appropriate for analyzing "grouped data"?

Various statistical methods are suitable for analyzing "grouped data", depending on the nature of the data and the research question. These include chi-square tests for categorical data, analysis of variance (ANOVA) for comparing means across groups, and regression analysis for examining relationships between variables. The choice of method depends on whether the data is nominal, ordinal, or interval-based.