Rolando Acosta and I recently posted a manuscript on bioRxiv describing the effects of Hurricane María, based on an analysis of mortality data provided by the Demographic Registry. I was also an author on a paper published in May based on a survey of 3…
Author: Simply Statistics
Divergent and Convergent Phases of Data Analysis
There are often discussions within the data science community about which tools are best for doing data science. The most recent iteration of this discussion is the so-called “First Notebook War”, which is well-summarized by Yihui Xie in his blog pos…
Being at the Center
Hilary Parker and I just released part 2 of our book club discussion of Nigel Cross’s book Design Thinking and it centers around a profile of designer Gordan Murray, who spent his career designing Formula One race cars. One of the aspects of his job …
Constructing a Data Analysis
This week Hilary Parker and I have started our “Book Club” on Not So Standard Deviations where we will be discussing Nigel Cross’s book Design Thinking: Understanding How Designers Think and Work. We will be talking about how the wo…
The Law and Order of Data Science
One conversation I’ve had a few times revolves around the question, “What’s the difference between science and data science?” If I were to come up with a simple distinction, I might say that
Science starts with a question; data science starts with …
The Trillion Dollar Question
Recently, Apple’s stock price rose to the point where the company’s market valuation was above $1 trillion, the first U.S. company to reach that benchmark. Subsequently, numerous articles were published describing Apple’s journey to this point and wh…
Why I Indent My Code 8 Spaces
Jenny Bryan recently gave a wonderful talk at the Use R! 2018 meeting in Brisbane about “Code Smells and Feels” (I recommend you watch a video of that talk). Her talk covers various ways to detect when your code “smells” and how to fix those smells thr…
Partitioning the Variation in Data
One of the fundamental questions that we can ask in any data analysis is, “Why do things vary?” Although I think this is fundamental, I’ve found that it’s not explicitly asked as often as I might think. The problem with not asking this qu…
Teaching R to New Users – From tapply to the Tidyverse
Abstract
The intentional ambiguity of the R language, inherited from the S language, is one of its defining features. Is it an interactive system for data analysis or is it a sophisticated programming language for software developers? The ability of…