Linear Correlation
Linear regression vs Pearson product vs Spearman rank coefficient
Linear Regression
Usually when the independent variable is fully controlled1
- 1 independent variable (x)
- 1 dependent variable (y)
Purpose: estimation of y-values from x-values
Pearson Product Moment Correlation (r)
Read more about Pearson Product Moment Correlation (r)
Generally applied when both variables are observed1
2 continuous random variables
Purpose: Correlation Coefficient
- Measure strength of the relationship
- Conventionally applied when both
Spearman Rank Coefficient ( )
Read more about Spearman Rank Coefficient (
- 2 Continuous random variables
- 1 variable is ordinal and ranked
- Converts non-linear to ranked-linear
Purpose: Correlation Coefficient
References
1.
Schober P, Boer C, Schwarte LA. Correlation Coefficients: Appropriate Use and Interpretation. Anesthesia and Analgesia. 2018;126(5):1763-1768. doi:10.1213/ANE.0000000000002864
Citation
For attribution, please cite this work as:
Yomogida N, Kerstein C. Linear Correlation. https://yomokerst.com/The
Archive/Evidene Based Practice/Multivariate Data
Analysis/Correlation/linear_correlation.html