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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
Neural Networks with torch: Revisiting the Abalone Data
Published:
This post demonstrates building and fitting a neural network using the torch package in R. In this post, I revisit the abalone Kaggle competition, which is a supervised regression problem described and analyzed in a previous blog post using tidymodels.
Analysis Walkthrough: Supervised Classification with Bank Churn Data
Published:
This post provides a walkthrough demonstrating how to use the sklearn package in Python to tune and evaluate multiple supervised classification methods, such as logistic regression and extreme gradient boosting (XGBoost) to predict whether bank customers will close their account. The dataset comes from a past Kaggle competition and contains several variables, including credit score, gender, and age.
Central Limit Theorem and Normal Approximations
Published:
This post discusses the classical Central Limit Theorem and demonstrates its usage through the Normal approximation of the Binomial distribution with a Shiny app.
Hypothesis Testing: Error Types and Power
Published:
This post discusses type I and type II errors, along with power. Basic background knowledge regarding hypothesis testing and $p$-values is assumed in this post.
Basics of Hypothesis Testing
Published:
This post explains the basics of hypothesis testing and provides a simple hypothetical pharmaceutical example of testing whether a new drug is better than an existing drug.
Analysis Walkthrough: Supervised Regression with Abalone Data
Published:
This post provides a complete walkthrough of analyzing Abalone data from Kaggle and applying supervised machine learning (ML) regression methods in R using the tidymodels package. The best model is selected from a suite of candidate models, including random forests and extreme gradient boosting (XGBoost).
Common Multivariate Control Charts
Published:
This post introduces basic overviews and examples of two of the most common multivariate statistical process monitoring (MSPM) methods: the $T^2$ and MEWMA control charts.
Multivariate Fault Detection with MSPM
Published:
This post introduces multivariate fault detection with multivariate statistical process monitoring (MSPM) and discusses its benefits over univariate methods.
Fault Detection with Statistical Process Control
Published:
This post gives a basic introduction to fault detection with statistical process control (SPC), also referred to as statistical process monitoring (SPM).
Oneway ANOVA Example
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This post provides a simple example of a oneway ANOVA using the ToothGrowth dataset in R. More detailed information about the oneway ANOVA model and how it works can be found here.
An Introduction to Analysis of Variance (ANOVA)
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This post gives a brief introduction to the basics of analysis of variance and how it works. An overview of the oneway analysis of variance model is provided along with additional details regarding sums of squares. A simple example of analysis of variance can be found here.
apps
Central Limit Theorem: Normal Approximation to the Binomial and Poisson Distributions
Published:
This shiny app visually demonstrates the effects of binomial and Poisson parameters on the normal approximation. It can be viewed in full-screen at this link.
Control Charts for VAR(1) Simulated Data
Published:
This shiny app displays simulated data and fitted classical and robust control charts for VAR(1) data, illustrating the effects of contamination during Phase I on control chart performance. It can be viewed in full-screen at this link.
Fit and Evaluate Machine Learning Models
Published:
This shiny app allows users to tune, fit, and evaluate the performance of various machine learning (ML) models using a default or custom (uploaded) dataset. It can be viewed in full-screen at this link. Code for the app can be found here.
portfolio
Portfolio item number 1
Published:
Short description of portfolio item number 1
Portfolio item number 2
Published:
Short description of portfolio item number 2
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.