correlational analysis

USAGE SUMMARY

"correlational analysis" is a correct and usable phrase in written English.
It refers to the statistical technique of examining the relationship between two or more variables. Example: "The researcher conducted a correlational analysis to determine the strength of the relationship between income and education levels in the population."

✓ Grammatically correct

Science

Academia

News & Media

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

Table 1 shows the results of the correlational analysis using Pearsons Correlation coefficients, between the PSOCQ subscales.

BMC Musculoskeletal Disorders

Bivariate non-parametric correlational analysis was undertaken to compute Spearaman Rank Correlation Coefficient.

BMC Musculoskeletal Disorders

When correlational analysis was used, gender, age, education and depression were significantly correlated with AUCG.

BMC Musculoskeletal Disorders

A similar correlational analysis was undertaken for NREM sleep.

Nature

This research uses a correlational analysis.

Procedia - Social and Behavioral Sciences

Correlational analysis of five commonly used measures of mental status/functional abilities in patients with Alzheimer disease.

Harvard University

In a correlational analysis, Ss who reported pronounced stimulant-like effects of alcohol (0.8 g/kg) also reported some greater stimulant-like effects of AMPH (20 mg).

Nature

Correlational analysis revealed two trends with regard to how these regulative activities impacted learning outcomes.

Computers in Human Behavior

In correlational analysis, like those in the literature, one must always be concerned that there is some third factor that could be associated with both the name and the outcome.

The New York Times

It is using quantitative research i.e. correlational analysis between two variables namely appreciation of historical building and visitor behaviour.

Procedia - Social and Behavioral Sciences

The results of correlational analysis are shown in Table 5.

European Transport Research Review

Expert writing Tips

Best practice

When writing about research, clearly specify the type of correlational analysis used (e.g., Pearson's, Spearman's) to enhance clarity and methodological rigor.

Common error

Avoid implying causation solely based on correlational findings. Clearly state that "correlational analysis" only demonstrates a relationship, not a cause-and-effect link, to prevent misinterpretations.

Linguistic Context

The phrase "correlational analysis" functions as a noun phrase referring to a specific statistical method. As Ludwig AI confirms, it's used to examine the relationship between two or more variables. The examples show its use in describing research methodologies and results.

Expression frequency: Very common

Frequent in

Science

75%

Academia

15%

News & Media

5%

Less common in

Formal & Business

3%

Encyclopedias

1%

Wiki

1%

Ludwig's WRAP-UP

In summary, "correlational analysis" is a very common and grammatically correct term used to describe a statistical method for examining relationships between variables. As Ludwig AI states, it accurately describes this technique. It is most frequently encountered in scientific and academic writing, where precision and methodological rigor are essential. When using "correlational analysis", it is crucial to avoid implying causation and to clearly specify the type of correlation being assessed. Alternative phrases like "correlation study" or "relationship analysis" may be suitable depending on the context.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

statistical correlation

This explicitly specifies that the correlation is being measured statistically.

correlation study

This alternative focuses on the study itself rather than the analytical process.

correlation assessment

This option emphasizes evaluating the strength and direction of relationships.

relationship analysis

This phrase broadens the scope to include any type of relationship, not just statistical correlations.

association analysis

Similar to relationship analysis, but specifically focuses on the degree of association.

dependence analysis

This term highlights the aspect of how one variable relies on another.

covariance analysis

This focuses on the measure of how two variables change together.

regression analysis

This approach uses a specific statistical method to model relationships.

causal analysis

This implies an investigation into cause-and-effect relationships, beyond simple correlation.

multivariate analysis

This alternative considers multiple variables and their interrelationships simultaneously.

FAQs

How is "correlational analysis" used in research?

In research, "correlational analysis" is used to determine the statistical relationship between two or more variables. It measures the extent to which changes in one variable are associated with changes in another, but it does not establish causation.

What are some alternatives to "correlational analysis"?

You can use alternatives like "correlation study", "relationship analysis", or "association analysis" depending on the specific context and focus of your analysis.

What is the difference between "correlational analysis" and causal inference?

"Correlational analysis" identifies statistical relationships between variables, while causal inference aims to determine if one variable causes changes in another. Correlational findings can suggest possible causal relationships, but further experimentation is needed to confirm causation.

When should I use a specific type of "correlational analysis", such as Pearson's or Spearman's?

Use Pearson's correlation when you have normally distributed data and want to measure linear relationships. Use Spearman's correlation when your data is not normally distributed or when you want to measure monotonic relationships (where the variables tend to move in the same direction, but not necessarily at a constant rate).