
Classification
Classification models are used to predict a categorical response.

Book Reviews!
No spoilers.

Basic Data Visualization in R
In which we review the fundamentals of creating graphs in R with ggplot2.

Basic Data Transformation in R
In which we review the fundamentals of transforming data in R, using six key functions in the dplyr package: filter, arrange, select, mutate, summarize, and group by.

Basic Data Exploration in R
In which we examine some common practical examples of data exploration: observing variance and covariance with histograms, boxplots, scatterplots, and heat maps.

HighLevel Data Wrangling in R: Imports, Pivots, and Joins
In which we go over importing data into R, working with 'tidy data,' manipulating single tables, and joining related tables.

Data Wrangling in R: Strings
In which we dive into string manipulation, with a focus on regular expressions.

Data Wrangling in R: Factors
In which we review some basic information about factors, a type of data used work with categorical variables.

Data Wrangling in R: Dates and Times
In which we review basic information about dates and times, including how to create them, how they are represented, and what you can do with them.

Programming in R: Pipes, Functions, and Vectors
In which we explore the basics of programming in R by examining common programming tools, data structures, and strategies to help effectively analyze data.

Programming in R: Iteration
In which we explore the basics of iteration through the lenses of functional and imperative programming by examining for loops, map functions, and more.

Model Building in R
In which we explore the basics of modeling as an exploratory tool through recording and graphing predictions and residuals, variable interactions, and transformations.

Notes on 'Winners Take All' by Anand Giridharadas
Winners Take All: The Elite Charade of Changing the World was published in 2018 and investigates how the global elite's efforts to change the world preserve the status quo and obscure their role in causing the problems they later seek to solve. In this post, I attempt to summarize his core argument.

Creating Simple Documents with R Markdown
In which we review the basics of R Markdown files, including the YAML header, code chunk options, and formatting options.

Graphing in R for Effective Communication
In which we review graphing options in ggplot2 that allow you to communicate results effectively, including labels, annotations, scales, zooming, and themes.

A List of Favorites, circa 2017
On my previous personal site, I had a page with some of my favorite things at the time. Here are those things.

Five things I learned from my first job out of college
I worked at a large technology company in a technical, customerfacing role for three years after I graduated from college. Here are the most important lessons I've taken from my experience.

An Introduction to Statistical Learning

Linear Regression
Linear Regression is a simple approach for predicting a quantitative response, and is the foundation of many other types of statistical learning. It is especially convenient for establishing a the strength of relationships between specific variables to an output, and is easily interpretable.

Blog Index: Start Here
An introduction to this blog, and a list of all my posts.
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