Publications by Christian Thieme
Inference, Prediction, and Explanation with Linear Regression
Simple Linear Regression: Inference, Prediction, Explanation A Modern Approach to Regression with R Linear Models with R Christian Thieme 2/17/2021 Simple Linear Regression: Inference, Prediction, Explanation A Modern Approach to Regression with R Exercise 2.3 The manager of the purchasing department of a large company would like to develo...
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Knowledge and Visual Analytics Final Project Proposal
The Purpose 🐔 Simulation ⚙️ The Data 💻 Why Streamlit ❓ Knowledge and Visual Analytics Final Project Proposal Christian Thieme 3/26/2021 The Purpose 🐔 Over the past decade, the desire for all natural, fresh, and organic food has grown exponentially. Significantly more offerings at grocery stores as well as the abundance of fa...
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Understanding Classification Metrics
Authorship Critical Thinking Group 1: Angel Claudio, Bonnie Cooper, Manolis Manoli, Magnus Skonberg, Christian Thieme and Leo Yi Background In the following exercises we will be working with a version of a well known dataset known as the “Pima Indians Diabetes Database”. The dataset was gathered by the National Institute of Diabetes and Dig...
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Understanding Linear Regression Output in R
Understanding Linear Regression Output in R Christian Thieme 3/10/2021 Regression is an incredibly common form of analysis used by both amateurs and professionals alike. Why is that? Because it is a robust tool for understanding relationships between variables. In addition, it also allows us the ability to make predictions on previously unseen d...
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Moneyball Multiple Regression Analysis
AUTHORSHIP Critical Thinking Group 1: Angel Claudio, Bonnie Cooper, Manolis Manoli, Magnus Skonberg, Christian Thieme and Leo Yi BACKGROUND On Sabermetrics Statistics have played a role in quantifying baseball since Henry Chadwick introduced the box score in 1858. The box score was adopted from cricket scorecards and introduced metrics ...
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Understanding Common Classification Metrics - Titanic Style
Understanding Common Classification Metrics - Titanic Style Introduction Evaluation Metrics The Model Evaluating our Model Accuracy Classification Error Rate Precision Sensitivity (Recall) Specificity Conclusion Christian Thieme 3/31/2021 Understanding Common Classification Metrics - Titanic Style Introduction After successfully generating ...
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Logistic Regression - Identifying High Risk Neighborhoods
Authorship Critical Thinking Group 1 Angel Claudio Bonnie Cooper Manolis Manoli Magnus Skonberg Christian Thieme Leo Yi Background In the following exercises we will be working with The Boston Housing Dataset. The dataset was gathered by the US Census Bureau regarding housing in the Boston Massachussetts area and can be obtained from the StatLi...
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CODE APPENDIX - COVID-19 Effect on Pneumonia & Influenza
Methods Dependancies library( dplyr ) library( ggplot2 ) ## Warning: package 'ggplot2' was built under R version 4.0.5 library( gridExtra ) library( rvest ) library( tidyverse ) library( multcompView ) ## Warning: package 'multcompView' was built under R version 4.0.5 library( cdcfluview ) ## Warning: package 'cdcfluview' was built under R v...
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Identifying Outliers in Linear Regression - Cook's Distance
Removing Outliers with Cook’s Distance Christian Thieme 5/14/2021 Understanding How to Use Cook’s Distance to Remove Outliers There are many techniques to remove outliers from a dataset. One method that is often used in regression settings is utilizing Cook’s Distance. Cook’s distance is an estimate of the influence of a data point. It t...
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Poisson, quasi-Poisson, Negative Binomial, and Zero Inflated Regression
Authorship Critical Thinking Group 1 Angel Claudio Bonnie Cooper Manolis Manoli Magnus Skonberg Christian Thieme Leo Yi Abstract We will explore, analyze and model a data set containing approximately 12,000 records representing various commercially available wines. The variables are primarily related to the chemical properties of the wine bein...
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