Open Access. Powered by Scholars. Published by Universities.®

Applied Statistics Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 4 of 4

Full-Text Articles in Applied Statistics

An Analysis Of The Success Of Farmers Markets In Kentucky Using Logistic Regression And Support Vector Machines, Jeron Russell Jan 2020

An Analysis Of The Success Of Farmers Markets In Kentucky Using Logistic Regression And Support Vector Machines, Jeron Russell

Mahurin Honors College Capstone Experience/Thesis Projects

The purpose of this research is to look at the relationship that market-specific, economic, and demographic variables have with the success of farmers markets in Kentucky. It additionally seeks to build a tool for predicting farmers market success that could be used by policy makers to aid in decision-making processes concerning farmers markets. Logistic regression and Support Vector Machines (SVMs) are used on data acquired from the Kentucky Department of Agriculture and the American Community Survey in order to analyze the data in a traditional statistical approach as well as a machine learning approach. The results included an SVM model …


Empirical Methods For Predicting Student Retention- A Summary From The Literature, Matt Bogard May 2011

Empirical Methods For Predicting Student Retention- A Summary From The Literature, Matt Bogard

Economics Faculty Publications

The vast majority of the literature related to the empirical estimation of retention models includes a discussion of the theoretical retention framework established by Bean, Braxton, Tinto, Pascarella, Terenzini and others (see Bean, 1980; Bean, 2000; Braxton, 2000; Braxton et al, 2004; Chapman and Pascarella, 1983; Pascarell and Ternzini, 1978; St. John and Cabrera, 2000; Tinto, 1975) This body of research provides a starting point for the consideration of which explanatory variables to include in any model specification, as well as identifying possible data sources. The literature separates itself into two major camps including research related to the hypothesis testing …


Empirical Methods-A Review: With An Introduction To Data Mining And Machine Learning, Matt Bogard May 2011

Empirical Methods-A Review: With An Introduction To Data Mining And Machine Learning, Matt Bogard

Economics Faculty Publications

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.


Monopoly, Regulation, And Innovation, Matt Bogard Mar 2010

Monopoly, Regulation, And Innovation, Matt Bogard

Economics Faculty Publications

Recently the Justice department has started investigations into alleged anti-trust violations by Monsanto. This has helped fuel a lot of already hyped discontent with one of the world’s leaders in innovative solutions for sustainable agriculture. This article discusses how the regulatory environment could possibly have contributed to more concentration and power in the biotech industry. Increasing regulation would likely have the opposite effect of creating a level playing field in the agriculture industry. From AgWeb, March 27,2010 http://www.agweb.com/blog/Economic_Sense_190/Monopoly_Regulation__and_Innovation_10771/