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[An algol program for the computation of empiric regressions]
Gegenbaurs Morphologisches Jahrbuch
|January 1, 1977
Summary
Empirical regression simplifies complex biological data analysis, aiding in functional relationship discovery for scattered measurements. This biomathematical tool assists researchers in deriving analytical expressions from data points.
Area of Science:
- Biomathematics
- Statistical Analysis
- Data Processing
Context:
- Handling large datasets in biological and medical research.
- Initial stages of data processing after measurements.
- Dealing with high dispersion in measured values.
Purpose:
- To explain the meaning and application of empirical regression.
- To provide a basis for functional relationship analysis.
- To guide the selection of appropriate empirical mathematical functions.
Summary:
- Empirical regression is a biomathematical-statistical procedure for data handling and initial processing, particularly with large datasets.
- It aids in identifying functional relationships and selecting mathematical functions when measured values are highly dispersed.
- The abstract details an ALGOL program for empirical regression, including user-friendly guidance for biological/medical professionals.
Impact:
- Enables researchers to derive analytical expressions for complex data.
- Facilitates data analysis without requiring advanced mathematical or computational expertise.
- Supports the adaptation of the empirical regression program for specific biological and medical research problems.