Welcome to the Congruent Connections faculty data scraper and DA 5020 Final Project for Stephen Holsenbeck. This page provides the in-depth documentation and write-up for how each modular function in the scraper works. In the navigation menu above, the Shiny Apps dropdown menu will take you to the Shiny App deployments on shinyapps.io. The Shiny Apps will allow you to browse professors in the data set by wordclouds, or to search the dataset by your interests, and return professor’s information whom match your interests. This data is searchable and downloadable. Note: The code and apps were tested on Windows 10 home running Chrome browser maximized to the screen, and the page coding is optimized for viewing in a maximized browser window on a desktop (though it uses bootstrap fluid formatting, so it can be viewed on smaller screens, though not optimally.)
Ridge, Elastic Net, and Lasso regression v Linear Regression Simple Vector Machines (SVM) v Logistic Regression Dataset on student performance
This homework covers Principal Component Analysis, Factor Analysis, KMeans Cluster Analysis and Hierarchical Cluster Analysis.
Multiple Linear Regression: Interaction Terms, Quadratic terms Binomial (logit) regression and prediction
Multiple Linear Regression, Quadratic and Interaction terms, Spurious and Chained, F-Test for Nested Models
Review of Function Writing, Probability, Graphing, Hypothesis Testing, Chi-Squared, F-Test
This is Homework 7 on Covariation, Correlation, Bivariate Regression and a t-test of the correlation.
Chi Squared and ANOVA Tests in R
Procedural notes for how to perform ANOVA & Chi Squared test.
Intro to computational Statistics, Homework 5, Question 4 uses some interesting data from the GSS https://gssdataexplorer.norc.org
Intro to Computational Statistics Homework 4
Intro to Computational Statistics - Homework 3
Homework 2 for PPUA 5301
This is homework 1 for PPUA 5301.