Empirical Methods-A Review: With an Introduction to Data Mining and Machine Learning
Abstract
This presentation was part of a staff workshop focused on empirical methods and applied research. This includes a basic overview of regression with matrix algebra, maximum likelihood, inference, and model assumptions. Distinctions are made between paradigms related to classical statistical methods and algorithmic approaches. The presentation concludes with a brief discussion of generalization error, data partitioning, decision trees, and neural networks.
Disciplines
Agribusiness | Agricultural and Resource Economics | Applied Statistics | Econometrics | Management Sciences and Quantitative Methods | Models and Methods
Recommended Repository Citation
Bogard, Matt, "Empirical Methods-A Review: With an Introduction to Data Mining and Machine Learning" (2011). Economics Faculty Publications. Paper 10.
https://digitalcommons.wku.edu/econ_fac_pub/10
Included in
Agribusiness Commons, Agricultural and Resource Economics Commons, Applied Statistics Commons, Econometrics Commons, Management Sciences and Quantitative Methods Commons, Models and Methods Commons