In our modern internet- and social media-connected society we are exposed to, if not inundated, with information. Information is all about data - the basic elements upon which a story is told, an event reported, an opinion formed. This explosion of data was supposed to give everyone more freedom of choice and opinion because we were, at least theoretically, more well-informed than we were in the past. A great challenge for the modern consumer of information is to truly understand the data, have a basic understanding of how that data was gathered or generated, how that data is presented to the reader or viewer, and how objective (or not) the conclusion drawn from that data actually is. Data can be used to manipulate and misinform, so it is critical for everyone to have a basic understanding of the nature of data.
As a scientist, I've been deeply trained in how to generate, analyze, and present data. The average person hasn't had that opportunity. In my lecture series, I present a wide-ranging introduction to the various elements of how data are generated, analyzed, and presented in plain language (and with as little math as humanly possible). I also present real-life examples of how data can be presented in both biased and unbiased ways. The goal of this lecture series is to give the participants tools for their toolkit that will help them understand the data they see, draw their own conclusions, and ask the critical question "what is missing from the data I've been shown and the conclusion I've been presented".