distribution analysis

USAGE SUMMARY

"distribution analysis" is a correct and usable phrase in written English.
It refers to the process of examining the frequency and distribution of a particular phenomenon or set of data. It is commonly used in various fields such as statistics, marketing, and finance. Example: The company conducted a distribution analysis to determine the most effective marketing strategy for their new product.

✓ Grammatically correct

Science

News & Media

Academia

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

This short paragraph outlines a mechanism for radically distributed storage, distribution, analysis, and reporting on the Diebold files.

Harvard University

Metro Market Studies California 2013 Grocery Distribution Analysis and Guide.

University of California, Berkeley

Genome-wide distribution analysis and KD of these H1 isoforms can help in validating this hypothesis.

Nature

The Heritage Foundation, which owns one, has not issued a distribution analysis.

The New York Times

Measuring membrane penetration with depth-dependent fluorescence quenching: distribution analysis is coming of age.

Nature

Its estimate is based on investment and spending indicators including property and car purchases, and on income distribution analysis.

The New York Times

Stacklies, W., Vega, M. C., Wilmanns, M. & Grater, F. Mechanical network in titin immunoglobulin from force distribution analysis.

Nature

The usefulness of the product distribution analysis was clearly demonstrated.

Catalysis Today

Anyone up for doing an income distribution analysis of salaries at UC? Would be interesting to see.

University of California, Berkeley

Animals scanned by MicroPET can subsequently be sacrificed and used for high-resolution tracer distribution analysis by DWBA.

Stanford University

To confirm the presence of dynamic averaging, we varied the time binning of the data and used Photon Distribution Analysis (PDA 38 to model the FD/FA distributions.

Nature

Expert writing Tips

Best practice

Specify the method or tool used for the "distribution analysis", such as statistical software or specific algorithms, to provide context and credibility.

Common error

Avoid using "distribution analysis" without specifying what is being analyzed. Always provide context to ensure the analysis is meaningful.

Linguistic Context

The phrase "distribution analysis" functions primarily as a noun phrase. It typically acts as the subject or object of a sentence, denoting the act or process of examining how data or elements are spread out. This is consistent with Ludwig and examples provided.

Expression frequency: Very common

Frequent in

Science

53%

Academia

17%

News & Media

13%

Less common in

Wiki

2%

Formal & Business

0%

Reference

0%

Ludwig's WRAP-UP

In summary, "distribution analysis" is a common and grammatically correct noun phrase that describes the examination of how data or elements are spread out. As Ludwig AI confirms, its purpose is to understand the patterns and characteristics of data. It is most frequently used in scientific and academic contexts, with authoritative sources like Nature and The New York Times providing numerous examples of its usage. Understanding best practices, such as clearly defining the scope of analysis, can further enhance its effectiveness in various applications.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

distribution assessment

Highlights the evaluation and judgment of how something is spread or dispersed.

statistical distribution

A more formal and mathematical term referring to the probability distribution of a variable.

dispersion analysis

Highlights the extent to which data points are scattered or spread out from a central value.

partitioning analysis

Focuses more on the division and separation of data into distinct groups or segments.

frequency analysis

Focuses specifically on the occurrence rate of different elements or events within a data set.

allocation analysis

Emphasizes the assignment or apportionment of resources or elements within a system.

segmentation analysis

Centers on dividing a market or population into distinct groups based on shared characteristics and distribution.

distribution testing

Specifically refers to the process of evaluating the distribution of software or products to ensure proper functionality.

profiling analysis

Involves creating a detailed characterization of a group or phenomenon based on its distribution patterns.

diffusion analysis

Implies the study of how something spreads or permeates through a medium or population.

FAQs

How is "distribution analysis" used in scientific research?

In scientific research, "distribution analysis" is used to examine the spread and frequency of data points, helping researchers identify patterns, trends, and anomalies. It's a fundamental step in understanding the characteristics of a dataset and drawing meaningful conclusions. For instance, it can be used in "spatial distribution analysis" to understand geographical patterns.

What are some common tools used for "distribution analysis"?

Common tools for "distribution analysis" include statistical software packages like R, SPSS, and SAS, as well as visualization tools like histograms, box plots, and scatter plots. These tools help in examining and interpreting the distribution of data.

How does "distribution analysis" differ from descriptive statistics?

"Distribution analysis" involves examining the entire spread and shape of a dataset, while descriptive statistics focus on summarizing the central tendency and variability of the data using measures like mean, median, and standard deviation. While descriptive statistics provide a snapshot, distribution analysis offers a more complete picture. You might use descriptive statistics as part of a "statistical distribution".

In what contexts is "distribution analysis" particularly useful?

"Distribution analysis" is valuable in fields like finance (analyzing investment returns), marketing (understanding customer demographics), and ecology (studying species distribution). It helps in making informed decisions based on the patterns and characteristics of the data being analyzed.