The course as I first encountered it followed what George Cobb termed the consensus curriculum (Cobb, 2007).
We talked about:
- means, medians, modes and standard deviations, variances, and ranges
- bar charts, pie charts, and histograms
- combinatorial and enumerative probability
- venn diagrams and probability rules
- the binomial, poisson, and normal probability distributions
- introduction to survey sampling
- the central limit theorem and sampling variability, estimation, confidence intervals, and hypothesis testing
- the one-sample Z test, the one-sample T-test, the paired T-test, the independent two sample T-test, the two-sample Z test, and chi-squared tests
- simple linear regression models
We tried to cram all this material into an 8-wk term, with only 6 weeks of instruction, and two weeks for exams and review. There were six homework assignments students completed, a midterm and a final exam, and students were asked to participate in discussion board activities.
It was an ambitious syllabus for sure. In my early enthusiasm, I saw no problem with it – if our students were here to learn statistics, then we should teach them statistics. I took AP Statistics when I was in high school, and obtained a Masters in Statistics, and this was how I was taught statistics.
Under the patient mentoring of my boss, the research core curriculum director, I slowly began to realize that (1) these were not valuable skills for our students, and (2) this was too confusing for our students.
I had forgotten that I barely understood statistics myself when I first encountered it. If I, someone who has had a lifelong love for numbers, didn’t fully understand statistics when I was taught it at the AP level, then how could I expect my students, mostly self-styled ‘not number people’, to reach a higher standard?
References and further reading:
Cobb, G. W. (2007). The introductory statistics course: A ptolemaic curriculum? Technology Innovations in Statistics Education, 1(1).