Data-science

Decision quality, problem solving, and data science

Decisions drive vision, strategy, execution, evaluation, problem-solving, performance, and continuous improvement.1 A decision is an irrevocable commitment of time and resources. Every decision has an opportunity cost—the loss benefit of the better option not chosen or not considered (see SDG.

Guide for setting up your Mac OS to write technical papers

My daughter is starting college this week. We bought her a Mac Book Air. This page is dedicated to first-year college students. Starting college (or graduate school) means doing a lot of homework, writing papers, citing your sources, and conducting calculations or technical analyses.

The Book of Why: The new science of cause and effect

Causal reasoning is at the core of everything we see, do, and imagine. Causal inference is the foundation of scientific thinking and reasoning. Every explicit decision we make is the realization of causal thinking.

Program theory is for the DAGs! (Part 2)

In Part 1 we introduced directed acyclic graphs (DAGs) [1] as a better way to represent program theory [2]. A DAG is a Bayesian network where each directed arrow represents a causal link, not merely a probabilistic dependency [3].

epitools: R tools for public health epidemiologists

Several years ago I (TJA) developed the ‘epitools’ R package for epidemiologic data and graphics. My goal was to have a practical package for practicing epidemiologists at local and state health departments.