id: 06326898
dt: j
an: 2014e.00783
au: Bargagliotti, Anna E.; Orrison, Michael E.
ti: A unifying framework for teaching nonparametric statistical tests.
so: PRIMUS, Probl. Resour. Issues Math. Undergrad. Stud. 24, No. 4, 309-318
(2014).
py: 2014
pu: Taylor \& Francis, Philadelphia, PA
la: EN
cc: K75
ut: introductory statistics; nonparametric statistics; Wilcoxon rank-sum test;
Friedman test
ci:
li: doi:10.1080/10511970.2013.876473
ab: Summary: Increased importance is being placed on statistics at both the
K-12 and undergraduate level. Research divulging effective methods to
teach specific statistical concepts is still widely sought after. In
this paper, we focus on best practices for teaching topics in
nonparametric statistics at the undergraduate level. To motivate the
work, we consider the problem of $n$ rankings: $m$ alternatives are
fully ranked by a sample of $n$ judges. Through this problem, we
addresses how to teach nonparametric methods under a unifying framework
that connects nonparametric methods to their parametric counterparts,
utilizes basic techniques from linear algebra, and can empower students
to make their own statistical tests.
rv: