data analysis

USAGE SUMMARY

"data analysis" is correct and usable in written English.
It can be used when referring to the process of examining data in order to draw conclusions or make decisions. For example, "Making decisions about our marketing strategy requires a thorough data analysis."

✓ Grammatically correct

Science

News & Media

Academia

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

51 human-written examples

participated in data analysis.

Nature

Data analysis and applications.

Nature

performed data analysis.

Nature

W.L.K. performed data analysis.

Nature

performed the data analysis.

Nature

SAGE Data Analysis SAGEE data analysis tool.

Stanford University

Human-verified similar examples from authoritative sources

Similar Expressions

9 human-written examples

"I'm a data-analysis person," Rosenfeld said.

Huffington Post

Results/Data Analysis.

University of California, Berkeley

Hands-on data analysis sessions.

Stanford University

Bayesian Data Analysis, CRC.

Harvard University

Econometrics and Data Analysis.

Yale University

Expert writing Tips

Best practice

Always consider your audience. If they are not technical experts, avoid jargon and explain analytical processes in plain language.

Common error

Don't mistake raw data outputs for meaningful insights. Always interpret and contextualize your "data analysis" to provide actionable conclusions.

Linguistic Context

The phrase "data analysis" functions primarily as a noun phrase, often serving as the subject or object of a sentence. It identifies the activity of examining data to extract meaningful insights. As Ludwig highlights, it's widely accepted and used in various contexts.

Expression frequency: Very common

Frequent in

Science

40%

News & Media

25%

Academia

20%

Less common in

Formal & Business

10%

Wiki

3%

Reference

2%

Ludwig's WRAP-UP

In summary, "data analysis" is a grammatically sound and highly prevalent term referring to the process of examining data for insights. As Ludwig AI confirms, it's widely accepted in English. Its frequency is very common, particularly in science, news, and academic contexts, with a source quality score of 89. Related phrases like "statistical analysis" and "data analytics" offer similar but nuanced meanings. When using the term, clarity in specifying data types and methods is crucial. A common pitfall is mistaking raw data for actual insights, necessitating careful interpretation.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

Data interpretation

Highlights the process of explaining the meaning of data.

Statistical analysis

Focuses specifically on the use of statistical methods in the analysis.

Data analytics

Emphasizes the use of technology and software to analyze data, often in a business context.

Trend analysis

Focuses specifically on identifying and interpreting trends in data.

Information processing

Broader term referring to the manipulation and transformation of information.

Data mining

Refers to the process of discovering patterns in large data sets.

Pattern recognition

Highlights the identification of patterns and trends within data.

Computational analysis

Emphasizes the use of computational methods in the analytical process.

Business intelligence

Focuses on using data analysis to inform business decisions.

Insights extraction

Focuses on the process of identifying and gathering insights from data.

FAQs

How is "data analysis" used in academic writing?

In academic writing, "data analysis" is used to present the methodical examination of research data, often involving statistical methods and critical interpretation of results. Example: "The study employed rigorous "statistical analysis" to validate its findings."

What's the difference between "data analysis" and "data analytics"?

"Data analysis" is the process of examining data to draw conclusions, while "data analytics" involves using software and technology to analyze data, often focusing on business applications.

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

Common tools for "data analysis" include software like Excel, SPSS, R, Python, and specialized business intelligence platforms, depending on the complexity and scale of the data.

How can I improve my "data analysis" skills?

To enhance your "data analysis" skills, focus on developing a strong foundation in statistics, learning to use data analysis software, and gaining practical experience through projects and real-world data sets.