linear correlation

USAGE SUMMARY

The phrase "linear correlation" is correct and usable in written English.
You can use this phrase to describe a relationship between two variables that vary proportionally - for example, "This data demonstrates the strong linear correlation between income level and educational attainment."

✓ Grammatically correct

Science

Academia

News & Media

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

The linear correlation coefficient has been used to quantify the magnitude of linear correlation.

Nature

The linear correlation coefficient=0.60 and the correlation probability=0.49%.

Nature

The null hypothesis of the linear correlation testing is: there is no linear correlation between two variables.

Nature

(c) Linear correlation of dCp values of SEC14L3 and FOXJ1 (n = 4 independent experiments).

Nature

Pearson's linear correlation coefficients were used to measure the dependency of two variables.

Nature

The corresponding linear correlation coefficients of −0.75 and −0.70 suggest reasonably strong negative correlations.

Nature

Lines show linear correlation fit, stairs show median values in respective bins.

Nature

The obtained linear correlation coefficient of −0.38 indicates a weak negative correlation.

Nature

Multiphysics simulations show a linear correlation of velocity with dipole moment near resonance.

Nature

The value of the LEDs is set with a simple linear correlation to the angle passed.

Cornell University

FITZSIMMONS: There has always been a steep linear correlation between socioeconomic background and test scores.

Harvard University

Expert writing Tips

Best practice

Use "linear correlation" when the relationship between two variables can be reasonably approximated by a straight line. If the relationship is curved, consider non-linear models.

Common error

Avoid implying that a "linear correlation" proves one variable causes the other. Correlation only indicates an association, not a causal link. Further evidence is required to establish causation.

Linguistic Context

The phrase "linear correlation" functions as a noun phrase, specifically denoting a statistical relationship between two variables. Ludwig AI confirms its widespread use in describing associations where a change in one variable corresponds proportionally to a change in another.

Expression frequency: Very common

Frequent in

Science

65%

Academia

20%

News & Media

5%

Less common in

Formal & Business

3%

Encyclopedias

2%

Reference

1%

Ludwig's WRAP-UP

The phrase "linear correlation" is a fundamental statistical term denoting a straight-line relationship between two variables. As Ludwig AI confirms, its usage is grammatically correct and very common across diverse fields, especially within scientific and academic research. The Pearson correlation coefficient is a key measure. While widely used, it's crucial to remember that correlation does not equal causation. For alternative phrasing, "direct relationship" or "linear association" provide similar meanings. Overall, understanding "linear correlation" is essential for interpreting statistical data and drawing informed conclusions.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

Pearson correlation

This is a specific type of linear correlation coefficient.

linear association

This term is a more formal way to describe a linear relationship.

linear dependence

This alternative suggests that one variable is predictable from the other in a linear fashion.

direct relationship

This phrase emphasizes the straightforward, proportional nature of the relationship.

straight-line relationship

This phrase uses more descriptive language to depict a linear relationship.

proportional relationship

This alternative highlights the consistent ratio between two variables.

positive correlation

This indicates that as one variable increases, the other also tends to increase linearly.

collinearity

This term refers to the state where two or more predictor variables are linearly related in a regression model.

statistical correlation

This is a broader term referring to any statistical relationship, linear or not.

covariance

While not exclusively linear, covariance measures how two variables change together.

FAQs

How is "linear correlation" measured?

The strength and direction of a "linear correlation" are typically quantified using the Pearson correlation coefficient, which ranges from -1 to +1. Values close to +1 indicate a strong positive correlation, values near -1 indicate a strong negative correlation, and values around 0 suggest a weak or no linear correlation.

What are some alternatives to "linear correlation"?

Depending on the context, you can use alternatives like "direct relationship", "linear association", or "Pearson correlation" to express a similar meaning.

Does "linear correlation" imply causation?

No, "linear correlation" does not imply causation. It only indicates a statistical association between two variables. A causal relationship requires additional evidence and cannot be solely determined from correlation.

What does it mean when there is no "linear correlation" between two variables?

If there is no "linear correlation" between two variables, it means that there is no straight-line relationship between them. However, it's important to note that there might still be a non-linear relationship.