statistical modeling

USAGE SUMMARY

The phrase "statistical modeling" is correct and commonly used in written English.
It refers to the process of creating mathematical models or representations to analyze and interpret data in a statistical manner. You can use "statistical modeling" when discussing data analysis methods, research studies, or in fields such as statistics, economics, and social sciences. Example: "The results of our study were analyzed using various statistical modeling techniques, including linear regression and logistic regression."

✓ Grammatically correct

Academia

News & Media

Science

Human-verified examples from authoritative sources

Exact Expressions

57 human-written examples

Statistical Modeling.

Stanford University

Statistical modeling, shape representation.

Massachusetts Institute of Technology

To compensate, they sometimes rely on extensive statistical modeling.

The New York Times

To avoid potential experimental confounding, various statistical modeling was used.

Nature

These results were calculated with a common statistical modeling method.

MIT Technology Review

Statistical Modeling of RNA-Seq Data.

Stanford University

Video structure segmentation with statistical modeling.

Columbia University

Statistical modeling and control in manufacturing processes.

Massachusetts Institute of Technology

For that reason, he said, his group moved on to advanced statistical modeling and data analyses.

The New York Times

THE next step was statistical modeling to estimate risks at lower levels of arsenic.

The New York Times

They used statistical modeling of the health survey population to make their comparisons.

The New York Times - Health

Expert writing Tips

Best practice

When discussing the creation or use of statistical models, use "statistical modeling". For example, "The study employed advanced statistical modeling techniques."

Common error

Avoid using "statistical modeling" interchangeably with general "data analysis". Statistical modeling is a specific subset of data analysis that involves creating a model to represent the data, while data analysis encompasses a broader range of techniques.

Linguistic Context

The phrase "statistical modeling" functions primarily as a noun phrase, often serving as a subject or object in a sentence. It refers to the process or methodology of creating statistical models. Ludwig AI indicates the phrase is correct and frequently used across many domains.

Expression frequency: Very common

Frequent in

Science

33%

Academia

32%

News & Media

21%

Less common in

Formal & Business

14%

Ludwig's WRAP-UP

In summary, "statistical modeling" is a grammatically sound and frequently used noun phrase that refers to the creation and application of mathematical models to data. Ludwig AI confirms its validity and widespread use. It's prevalent in academic, scientific, and news contexts, indicating a formal and technical register. The phrase serves to describe the methodology and is essential for discussing research, analysis, and prediction. Related phrases like "data modeling" and "predictive analytics" offer similar but nuanced perspectives. Understanding its correct usage and potential misinterpretations ensures clear and effective communication.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

statistical analysis

Encompasses a wide range of statistical techniques, including but not limited to modeling.

data modeling

Focuses more broadly on the representation and organization of data, while "statistical modeling" specifically uses statistical methods.

predictive analytics

Emphasizes the prediction aspect using statistical techniques; "statistical modeling" is the broader process.

probabilistic modeling

Uses probability theory to create models; it is a subset of "statistical modeling".

regression analysis

A specific type of statistical modeling focused on relationships between variables; "statistical modeling" includes other techniques.

econometric modeling

Applies statistical methods to economic data; "statistical modeling" is a more general term.

machine learning

Focuses on algorithms that learn from data; "statistical modeling" can be a component.

mathematical modeling

A broader category including non-statistical models; "statistical modeling" is a subset.

time series analysis

Specific to analyzing data points indexed in time order, while "statistical modeling" may or may not include this temporal aspect.

data mining

Focuses on discovering patterns in large datasets, and statistical models may be used.

FAQs

How is "statistical modeling" used in research?

"Statistical modeling" is used to create mathematical representations of data, allowing researchers to test hypotheses, make predictions, and understand relationships between variables. It can involve techniques like regression, ANOVA, and time series analysis.

What's the difference between "statistical modeling" and "data analysis"?

"Statistical modeling" is a subset of "data analysis" that focuses on building mathematical models to understand data. Data analysis is broader and includes techniques like data cleaning, visualization, and summary statistics.

When should I use "statistical modeling" over other analytical techniques?

Use "statistical modeling" when you want to create a model that represents the underlying processes generating your data. This allows you to make predictions, test hypotheses, and understand the relationships between variables in a formal and quantitative way. Other techniques, such as "exploratory data analysis", are more suitable for initial data exploration.

What are some common types of "statistical modeling"?

Common types of "statistical modeling" include linear regression, logistic regression, time series analysis, ANOVA, and Bayesian modeling. The specific type of model used depends on the nature of the data and the research question.