correlation strength

USAGE SUMMARY

"correlation strength" is correct and usable in written English.
You can use it to refer to the degree to which two or more variables are related to each other. For example, "The correlation strength between hours spent studying and exam scores was quite impressive."

✓ Grammatically correct

Science

Science & Research

Academia

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

The similarity indices for the full STRF were significantly correlated with correlation strength (Figure 12A: r = 0.444, p<0.01, N = 1203, t-test).

Plosone

We investigated whether the correlation sign of the miRNA expression with that of its targets is associated to a different proportion of correlated targets or a different correlation strength.

BMC Genomics

The nodes (fragments) are connected by edges when their conformational transitions are correlated, and the edge weight describes the correlation strength (Eq. 5).

FASEB Journal

Edges between nodes represent correlation strength (the thicker the line the more correlated the genes).

Nature

In addition, Pearson or Spearman correlations (as appropriate) were performed to obtain standard estimates of correlation strength (which are not provided by robust regression).

Nature

Assessment of correlation strength among input variables on the sensitivity analysis is also achieved.

Journal of Sound and Vibration

Specifically, eight CASH indicators (in order of correlation strength: Protein, ActC, Mn, Resp, AgStab, P, Mg, and OM) displayed significant linear relationships to mean corn yields (Figure 1).

Cornell University

We now build a 2-layer hierarchy by clustering the learned topics, with their learned correlation strength as the similarity measure.

Massachusetts Institute of Technology

Consequently, the effective electron correlation strength, given by the ratio between the bandwidth and the on-site Coulomb interactions, can be controlled to reach from the weak to the strong coupling regime.

Nature

(A) This figure shows the correlation strength (signed, negative log10 p-value: positive denotes a direct correlation) between 7 known gene markers of common brain cell types and the AD-related traits analyzed in this study.

Nature

(B) This figure shows the correlation strength between expression level of all genes with an AD-related trait before (x-axis) and after (y-axis) adjusting for 7 standard cell type markers (shown in Figure S3A).

Nature

Expert writing Tips

Best practice

When discussing statistical relationships, quantify "correlation strength" with specific metrics such as Pearson's r or Spearman's rho to provide precise and comparable information.

Common error

Avoid implying a cause-and-effect relationship solely based on strong "correlation strength". Always consider potential confounding variables and conduct further investigation to establish causality.

Linguistic Context

The phrase "correlation strength" functions as a noun phrase, specifically describing the degree or magnitude of a statistical relationship between two or more variables. As Ludwig AI confirms, it's grammatically sound and usable in academic and scientific writing.

Expression frequency: Very common

Frequent in

Science

40%

Science & Research

30%

Academia

20%

Less common in

News & Media

5%

Formal & Business

3%

Encyclopedias

2%

Ludwig's WRAP-UP

In summary, "correlation strength" is a common and grammatically correct noun phrase used to describe the degree of relationship between variables. Ludwig AI confirms its usability. It is most frequently found in scientific and academic contexts, with authoritative sources like Nature and PlosOne using it regularly. When writing about statistical relationships, quantifying the "correlation strength" with specific metrics is a best practice. Avoid implying causation solely based on correlation.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

degree of correlation

Emphasizes the extent to which two variables are related.

correlation coefficient magnitude

Focuses on the numerical value representing the strength of the correlation.

strength of association

Highlights the level of connection or dependence between variables.

level of correlation

Indicates the intensity or degree to which variables are correlated.

correlation intensity

Stresses the power or vigor of the relationship between variables.

degree of relatedness

Highlights how closely two or more items are connected.

magnitude of association

Emphasizes the numerical size of the relationship.

extent of correlation

Focuses on the range or scope of the relationship.

correlation effect size

Focuses on the magnitude of the impact of the correlation.

measure of association

Highlights the quantitative assessment of the relationship.

FAQs

How can I describe different levels of "correlation strength"?

You can use terms like "weak correlation", "moderate correlation", or "strong correlation" to describe different levels of "correlation strength". It's also helpful to provide the correlation coefficient (e.g., Pearson's r) to quantify the strength.

What factors might affect the observed "correlation strength" between two variables?

Several factors can influence "correlation strength", including sample size, measurement error, the presence of outliers, and non-linear relationships. Confounding variables can also mask or inflate the true relationship.

Is there a difference between "correlation strength" and statistical significance?

"Correlation strength" refers to the magnitude of the relationship between variables, while statistical significance indicates whether the observed correlation is likely due to chance. A strong correlation can be statistically insignificant with a small sample size, and a weak correlation can be statistically significant with a large sample size.

What are some alternative ways to express "correlation strength" in writing?

Depending on the context, you can use alternatives such as "degree of correlation", "strength of association", or "level of correlation". The best choice depends on the specific nuance you want to convey.