Despite the dearth of literature specifically on teaching statistics using social justice, there is precedent
in the more general realm of teaching using social justice, or even in teaching mathematics using social justice.
This article offers an overview of content examples, resources, and references that can be used in the specific
area of statistics education. Philosophical and pedagogical references are given, definitional issues are discussed,
potential implementation challenges are addressed, and a substantial bibliography of print and electronic resources
is provided.
Key Words: Critical Thinking; Ethics; Service Learning; Statistical Literacy; Statistical Thinking.
In the early 1990's, the National Science Foundation funded many research projects for improving statistical education.
Many of these stressed the need for classroom activities that illustrate important issues of designing experiments,
generating quality data, fitting models, and performing statistical tests. Our paper describes such an activity on logistic
regression that is useful in second applied statistics courses. The activity involves students attempting to toss a ball into
a trash can from various distances. The outcome is whether or not students are successful in tossing the ball into the trash
can. This activity and the adjoining homework assignments illustrate the binary nature of a response variable, fitting and
interpreting simple and multiple logistic regression models, and the use of odds and odds ratio
Key Words: Odds, Odds ratio; Problem solving.
The technique of distance sampling is widely used to monitor biological populations. This paper documents
an in-class activity to introduce students to the concepts and the mechanics of distance sampling in a
simple situation that is relevant to their own experiences. Preparation details are described. Variations
and extensions to the activity are also suggested..
Key Words: Estimation; Proportions; Sampling distribution; Statistical education.
Emphasis on problem solving in mathematics has gained considerable attention in recent years. While
statistics teaching has always been problem driven, the same cannot be said for the teaching of probability
where discrete examples involving coins and playing cards are often the norm. This article describes an
application of simple probability distributions to a practical problem involving a carÕs approach to a
red traffic light, and draws on the ideas of density functions, expected value and conditional distributions.
It provides a valuable exercise in applying theory in a practical context.
Key Words: Distributions; Modelling; Optimization; Problem solving.
This article gives an example of how student-conducted experiments can enhance a course in the design of experiments.
We focus on a project whose aim is to find a good mixture of water, soap and glycerin for making soap bubbles. This
project is relatively straightforward to implement and understand. At its most basic level the project introduces
students to mixture experiments and general issues in experimental design such as choosing and measuring an appropriate
response, selecting a design, the effect of using repeats versus replicates, model building, making predictions, etc.
To accommodate more advanced students, the project can be easily enhanced to draw on various areas of statistics, such
as generalized linear models, robust design, and optimal design. Therefore it is ideal for a graduate level course as
it encourages students to look beyond the basics presented in class.
Key Words: Constrained experimental region; Generalized linear model; Optimal design; Poisson regression;
Robust parameter design.
Announcing a New Department
A new section for the Journal of Statistics Education is introduced and a call for papers is made.
Key Words: Statistics Education Research.
Datasets and Stories
Three sets of rare baseball events Š pitching a no-hit game, hitting for the cycle, and turning a triple play Š
offer excellent examples of events whose occurrence may be modeled as Poisson processes. That is, the time of occurrence
of one of these events doesnÕt affect when we see the next occurrence of such. We modeled occurrences of these three events
in Major League Baseball for data from 1901 through 2004 including a refinement for six commonly accepted baseball eras
within this time period. Model assessment was primarily done using goodness of fit analyses on inter-arrival data.
Key Words: Anderson-Darling Goodness-of-Fit Test; Exponential Distribution; Hitting for the Cycle;
Memoryless Property; No-Hit Games; Poisson Process; Triple Plays.