statistical model

USAGE SUMMARY

The phrase "statistical model" is correct and usable in written English.
It is typically used in academic and scientific writing to refer to a mathematical representation of a system or phenomenon that is based on statistical principles and data. Example: "The researchers developed a statistical model to analyze the relationship between socioeconomic status and educational attainment."

✓ Grammatically correct

Science

News & Media

Academia

Human-verified examples from authoritative sources

Exact Expressions

55 human-written examples

It's still a statistical model, but at least the statistics are about people, rather than things.

The New Yorker

developed the statistical model.

Nature

A spatial statistical model for landscape genetics.

Nature

They came from the researchers' statistical model.

The New York Times - Health

A new look at the statistical model identification.

Nature

There's nothing magical about this one statistical model, of course.

The Washington Post

Human-verified similar examples from authoritative sources

Similar Expressions

5 human-written examples

In the case of statistics, researchers build statistical models.

Cornell University

Inventing new statistical models?

The New Yorker

Statistical Modeling.

Stanford University

J.A. led the statistical modelling.

Nature

Statistical Models in Genetics.

Stanford University

Expert writing Tips

Best practice

When describing the purpose of a "statistical model", be specific about the variables involved and the relationships being explored. Clarity enhances the model's interpretability and utility.

Common error

Avoid assuming a "statistical model" developed for one population or dataset is universally applicable. Always validate its performance on new, relevant datasets to ensure reliability and avoid biased conclusions.

Linguistic Context

The phrase "statistical model" functions as a noun phrase, typically serving as the subject or object of a sentence. It identifies a specific type of model used for statistical analysis. As shown by Ludwig, this model is a representation of relationships within data.

Expression frequency: Very common

Frequent in

Science

42%

News & Media

33%

Academia

15%

Less common in

Formal & Business

10%

Ludwig's WRAP-UP

The phrase "statistical model" is a common and grammatically correct term, widely used in scientific, academic, and news contexts to describe a representation of a system or phenomenon based on statistical data and principles. As Ludwig AI confirms, it's a valid and useful term in written English. While alternatives like "mathematical model" or "predictive model" exist, the specific choice depends on the context. When using a "statistical model", it's essential to clearly define the variables and relationships being explored and to validate the model's applicability to different datasets to avoid overgeneralization.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

probabilistic model

Emphasizes the use of probability theory in the model.

mathematical model

Replaces 'statistical' with 'mathematical', focusing on the mathematical aspect of the model rather than the statistical one.

machine learning model

Focuses on models developed using machine learning techniques.

predictive model

Emphasizes the model's ability to predict outcomes based on data.

analytical model

Replaces 'statistical' with 'analytical', emphasizing the use of analytical methods.

regression model

Specifies a type of statistical model used for regression analysis.

statistical framework

Emphasizes the conceptual structure rather than the specific model.

econometric model

Refers to a statistical model used in econometrics, focusing on economic data.

simulation model

Highlights the model's use for simulating real-world processes.

data model

General term for a model describing data structures and relationships, less specific than "statistical model".

FAQs

How is a "statistical model" used in research?

A "statistical model" is used to represent and analyze relationships between variables in a dataset, allowing researchers to test hypotheses, make predictions, and draw inferences about a population. Common examples include regression models, ANOVA, and time series analysis.

What are some alternatives to calling something a "statistical model"?

Depending on the context, you can use terms like "mathematical model", "predictive model", or "data model". The best choice depends on the specific characteristics and purpose of the model.

What makes a "statistical model" effective?

An effective "statistical model" accurately represents the underlying data, provides reliable predictions, and is interpretable. It should also be validated using appropriate statistical techniques to ensure its robustness and generalizability.

What's the difference between a "statistical model" and a machine learning model?

While both are used for prediction and inference, a "statistical model" typically relies on predefined statistical assumptions and aims for interpretability. A machine learning model, in contrast, often focuses on predictive accuracy and can handle more complex, non-linear relationships without strict assumptions. However, the line is increasingly blurred as machine learning incorporates statistical methods.