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I am going to teach this probability and statistics course in a couple of weeks. The probability part can be made very interesting, in my opinion, easily. But I am a little worried that I might make the statistics part a boring collection of information and algorithmic manipulations. So my question is, how do I make the statistics part of the course interesting?
The syllabus for the stat part is roughly the contents of this book.
Expanding a bit on my comment, there is (1) a new textbook available for project-based intro stats, (2) an online syllabus describing a course based on community projects, and (3) an academic paper concluding that "the project-based course ... provides a promising model for getting students hooked on the power and excitement of applied statistics."
(1) Chelsea Myers. Project-Based R Companion to Introductory Statistics. Routledge link.
(2) Cindy Kaus, Introductory Statistics with Community-Based Projects. Metropolitan link.
(3) Dierker, Lisa, Jane Robertson Evia, Karen Singer-Freeman, Kristin Woods, Janet Zupkus, Alan Arnholt, Elizabeth G. Moliski, Natalie Delia Deckard, Kristel Gallagher, and Jennifer Rose. "Project-based learning in introductory statistics: Comparing course experiences and predicting positive outcomes for students from diverse educational settings." International Journal of Educational Technology and Learning 3, no. 2 (2018): 52-64. Journal link.
That's pretty normal to have a lot of ground to cover. Even with the more friendly books, it still ends up being a lot of concepts and formulas. Given this, I think you sort of have to make your peace with the idea that kids will not master everything, especially in the long term. I probably wouldn't try some fundamental change to improve things since it may make things worse (like adding a big project or the like). Just engage with the kids, be animated and sort of cheerlead through the thing. Maybe tell a sea story or two.
Whereas I have an iconic recall of the quadratic formula, I don't think I've ever used a chi test in a class or business/engineering situation. And I don't remember the formula. Or what is different about it versus a t test. But at least I sorta "heard of it".
In terms of basic lasting concepts, I think they should have lasting knowledge that normal distribution is a "bell curve" and is a decent guess when you have no clue. Along with the very basic concepts of confidence intervals (not every tricky caveat or logic issue but just the idea of 90% CI).
After that, just the info that there are a lot of concepts, formulas, and things can be tricky. So if someone quotes a statistic know that it may have issues. And if you are working on something statistical, bring in a professional/watch out for errors. [But again, I know "rigor people" hate this, but I think you have to set the bar lower at "exposure" rather than "mastery". Pound smart, not penny foolish.]
