In many of the course lectures we will discuss how you can spot bullshit, call bullshit, and avoid becoming the victim of bullshit. Here we present a set of instructional essays on various aspects of bullshit detection and refutation. Many of the examples we draw upon are classic examples that others have brought to light in their articles, essays, blogs, and other sources.
Visualization: Spotting Misleading axes. Data graphics tell stories. Fairly subtle choices on the part of their creators can influence the stories they tell, sometimes in misleading fashion. We look at how the ranges shown on axes can be misleading, and explore the classic issue of when the y-axis of a graph needs to include zero.
How do you know a paper is legit? Any scientific paper can be wrong, but you greatly decrease the chances of being mislead if you know how to distinguish legitimate articles from untrustworthy ones. We discuss how to draw this distinction, and along the way provide a brief overview of how the scientific publication process works.