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In regression

Grammar usage guide and real-world examples

USAGE SUMMARY

The phrase "In regression" is correct and usable in written English.
It can be used in contexts related to statistical analysis, particularly when discussing regression analysis or models. Example: "In regression, it is important to check for multicollinearity among the independent variables."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

In regression models.

In regression (6), we control for manufacturing and schooling.

In regression 4, we only include immigration flows from two years prior.

In regression analysis, at first all seven predictor variables have been used.

In regression analyses, association of each variable with MIDAS score was examined.

In regression (5), we include both GDP and schooling as control variables.

In regression (7), we control for politics as well as the schooling variable.

In regression 6, all year fixed effects are removed from our model.

In regression 2, we only include lagged immigration flows from one year prior and its square.

In regression analyses, however, they were treated as continuous variables.

In regression analysis these items would most likely demonstrate collinearity.

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Expert writing Tips

Best practice

When using "in regression", clearly specify what aspect of the regression analysis you are referring to, such as variables, models, or results, to avoid ambiguity.

Common error

Avoid using "in regression" without context, as it can leave the reader unsure of the specific application or aspect being discussed. Always provide sufficient detail for clarity.

Antonio Rotolo, PhD - Digital Humanist | Computational Linguist | CEO @Ludwig.guru

Antonio Rotolo, PhD

Digital Humanist | Computational Linguist | CEO @Ludwig.guru

Source & Trust

82%

Authority and reliability

4.1/5

Expert rating

Real-world application tested

Linguistic Context

The phrase "In regression" functions primarily as a prepositional phrase that sets the context for a statement related to statistical analysis. Ludwig AI confirms its usability in discussing regression models and their components.

Expression frequency: Common

Frequent in

Science

70%

News & Media

15%

Formal & Business

10%

Less common in

Encyclopedias

2%

Wiki

2%

Social Media

1%

Ludwig's WRAP-UP

In summary, the phrase "in regression" is a grammatically sound and commonly used prepositional phrase that serves to contextualize discussions related to regression analysis. According to Ludwig AI, it is most frequently found in scientific and academic writing. To ensure clarity, always specify which aspect of the regression you are referencing and avoid overgeneralization. By following these guidelines, you can effectively use "in regression" to enhance the precision and clarity of your analytical writing.

FAQs

How is "in regression" typically used in academic writing?

In academic writing, "in regression" is used to specify the context of an analysis, such as "In regression analysis, we found..." or "In the regression model, the coefficient represents...". This helps provide clarity regarding the methods and findings.

What does it mean when a variable is 'significant' "in regression"?

When a variable is described as 'significant' "in regression", it means that the variable has a statistically significant impact on the dependent variable being analyzed. This significance is determined through hypothesis testing, with a p-value typically below a predetermined threshold (e.g., 0.05).

Which is more accurate, "within the regression" or "in regression"?

Both phrases are acceptable, but their nuance is different. "In regression" is a general reference to the process or analysis, while "within the regression" typically specifies an element being part of the regression itself.

Are there specific types of regressions where using the phrase "in regression" is more common?

The phrase "in regression" is generally applicable across various regression types (linear, logistic, etc.). However, it’s particularly useful when describing specific findings or considerations within a particular regression model or analysis, regardless of its type.

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Authority and reliability

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Most frequent sentences: