The Journal of Statistics Education

1. The Journal of Statistics Education An International Journal on the Teaching and Learning of Statistics

2. JSE Mission • To disseminate knowledge for the improvement of statistics education at all levels. It is distributed electronically and publishes articles that enhance the exchange of diversity of interesting and useful information among educators, practitioners, and researchers around the world.

3. Intended Audience and Peer Review • The intended audience includes anyone who teaches statistics, as well as those interested in research on statistical and probabilistic reasoning. • All submissions are rigorously refereed using a double-blind peer review process.

4. Potential Topics • Curricular reform in statistics • The use of cooperative learning and projects • Innovative methods of instruction • Assessment • Research on students’ understanding of probability and statistics • Research on the teaching of statistics, attitudes and beliefs about statistics

5. Potential Topics (Continued) • Creative and tested ideas for teaching probability and statistics topics • The use of computers and other media in teaching statistics • Statistical literacy • Distance education

6. Potential Topics (Continued) • New ways of looking at statistical topics that teachers would find useful. • Articles that provide a scholarly overview of the literature on a particular topic are also of interest.

7. Recently Published Articles • G. Rex Bryce (2005), “Developing Tomorrow’s Statisticians,” 13(1). • Barbara Ward (2004), “The Best of Both Worlds: A Hybrid Statistics Course,” 12(3). • Ulf Olsson (2005), “Confidence Intervals for the Mean of a Log-Normal Distribution,” 13(1).

8. Recently Published Articles • Timothy S. Vaughan and Kelly E. Berry (2005), “Using Monte Carlo Techniques to Demonstrate the Meaning and Implications of Multicollinearity,” 13(1). • Mary Richardson, John Gabrosek, Diann Reischman, and Phyllis Curtis (2004), “Morse Code, Scrabble and the Alphabet,” 12(3).

9. Data Sets and Stories • Robert W. Hayden (2005), “A Data Set that is 44% Outliers,” 13(1). • David E. Kalist (2004), “Data from the TV Show Friend or Foe?,” 12(3). • Neil Binnie (2004), “Using EDA, ANOVA and Regression to Optimise some Microbiology Data,” 12(2).

10. What Not to Submit. • Articles that deal entirely with a theoretical result, its derivation and proof. • Articles on educational statistics that do not deal with teaching of statistics. • Articles that describe analysis of data in a particular field if the focus of the article is on the analysis of the data for consumption by researchers in other disciplines.

11. Common Mistakes to Avoid • Multiple spelling and grammatical errors. • Incomplete and/or obvious mistakes in the references. • A narrow or biased review of the literature. • Inappropriate data analysis.

12. Raising the Bar. • Activities should model good statistical practice. • Studies should be well planned and well executed. • Good assessment of student outcomes.