Abstract
The mathematics behind two statistical methods used for prediction are developed: principal component analysis and naive Bayesian classifier. Principal component analysis uses variables from a data set to create a smaller number of new, uncorrelated variables. The naive Bayesian classifier method predicts which class each sample in a data set belongs to based on an independence assumption, conditional probabilities, and Bayes' theorem. To illustrate each method we implement to predict first year retention for College of Wooster students. The data from College of Wooster students is used to show how the methods are implemented and how results from each method are analyzed.
Advisor
Ramsay, John
Department
Mathematics
Recommended Citation
Angelo, John, "Predictive Analytics on First Year Retention at the College of Wooster" (2013). Senior Independent Study Theses. Paper 960.
https://openworks.wooster.edu/independentstudy/960
Disciplines
Applied Mathematics
Publication Date
2013
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2013 John Angelo