I apologize for our absence over the last several weeks. Though it was my intention to work on “tackling the tough concepts in statistics.” I’ve, instead, been tackling the tough concepts of life and death, as my father died following a battle with cancer. However, though I miss my Dad tremendously, it is time to continue with this blog.
Last year, I posed a question to the sages … What are the critical concepts in applied statistics. Their response was an overwhelming … it’s not a matter of individual concepts but the overall application of statistics that is necessary for true understanding.
Of course, I wholeheartedly support this assertion, and yet, as I look at how people come across this blog, they almost always do so by searching for specific statistical concepts. I also have to argue that we have to make sure students understand certain concepts before they can grasp the larger application of statistics. Taken together, I think it is a worthwhile endeavor for a few blogs to be focussing on how to teach the critical concepts in statistics.
A search of the literature failed to yield a complete list of concepts. However, when looking at the website CAUSEweb.org, the Consortium for the Advancement of Undergraduate Statistics Education, they have resources on statistical concepts divided into eight sections, and I added one. Those concepts are Data, Central Tendency, Correlation and Covariation, Distribution and Graphs, Variability, Sampling, Sampling Distribution, and Inferences. However, I would also add to this list, Error, as though it overlaps with several of the prior concepts, it is a critical concept that requires direct attention.
Over the next several weeks, I will be addressing each of these concepts and provide information on how to best teach it. Of course, if you feel I’m missing a concept, I encourage you to let us know.