The rank transformation-an easy and intuitive way to connect many nonparametric methods to their parametric counterparts for seamless teaching introductory statistics courses

2012 ◽  
Vol 4 (5) ◽  
pp. 432-438 ◽  
Author(s):  
W. Jay Conover
1996 ◽  
Vol 50 (2) ◽  
pp. 159 ◽  
Author(s):  
Arnold J. Stromberg ◽  
Subathra Ramanathan

1987 ◽  
Vol 14 (1) ◽  
pp. 20-23 ◽  
Author(s):  
Herbert Friedman

In order to reduce test anxiety and to encourage the learning of course material, students were given the opportunity to offset a poor lecture examination grade by taking a second, equivalent exam. The repeat exam provided immediate reward for using the initial exam as a study guide. Students who took two or three repeat exams had higher final examination grades than those who took fewer repeats. The repeat exam procedure was well received by all students, helped weaker students to keep up with the course, and was convenient for the instructor to implement.


1974 ◽  
Vol 67 (2) ◽  
pp. 123-126
Author(s):  
Gottfried E. Noether

Introductory statistics courses are taken each year by hundreds of thousands of students across the country. These students come from many fields: the life sciences, humanities, education, agriculture, business, but above all from the social sciences. They rarely take statistics voluntarily. They sign up for the course because of departmental or graduation requirements. The great majority has minimal preparation in mathematics, rarely more than they bring along from high school. They carry over into statistics their prejudices of mathematics and quite often, justifiably so. Teachers of statistics courses should then ask themselves how they can make the introductory statistics course statistically meaningful and not simply an exercise in mathematics or, what may even be worse, a meaningless compendium of statistical techniques.


2015 ◽  
Author(s):  
Emily Michele Casleton ◽  
Ulrike Genschel

1989 ◽  
Vol 16 (2) ◽  
pp. 67-68 ◽  
Author(s):  
David E. Johnson

A significant number of students in introductory statistics courses may function at Piaget's concrete operational level of thought. These students may find it difficult to understand the complex correlations and interactions between variables that typify many statistical procedures. A technique for introducing analysis of variance (ANOVA) in a concrete fashion is presented. This technique leads students to an intuitive understanding of the concepts of between- and within-groups variance and their relationship to each other.


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