This article describes an assessment activity that can show students how much they intuitively understand about statistics, but also alert them to common misunderstandings. How the activity can be used formatively to help improve students' conceptual understanding of analysis of variance is discussed. (Contains 1 figure and 1 table.)

We consider three examples from our own teaching in which much was learned by critically examining examples from books. Even influential and well-regarded books can have examples where more can be learned with a small amount of additional effort. (Contains 3 figures.)

This article re-examines the much maligned piechart and provides justification for its use. It identifies common pitfalls when drawing piecharts in Microsoft Excel and offers advice on how to avoid them. (Contains 6 figures and 5 tables.)

This article studies various holiday distributions, the most interesting one being Easter. Gauss' Easter algorithm and Microsoft Excel are used to determine that the Easter distribution can be closely approximated by the convolution of two well-known uniform distributions. (Contains 8 figures.)

In this article, the authors focus on hypothesis testing--that peculiarly statistical way of deciding things. Statistical methods for testing hypotheses were developed in the 1920s and 1930s by some of the most famous statisticians, in particular Ronald Fisher, Jerzy Neyman and Egon Pearson, who laid the foundations of almost all modern methods of…

The statistical thinking exhibited by 14-19 year-old students during clinical interview sessions is described. The students' thinking with regard to fundamental statistics concepts is reported in order to help inform instructional practice.

This article presents two different approaches to studying the accuracy and precision of a measurement.

The mean and variance of the number of turning points in random permutations are evaluated. These results are applied to a test of randomness of fluctuations.

This article describes an activity through which students collect data and explore ways to display them through graphs and charts. It also motivates various summary measures for location, spread and shape. Finally, it gives an introduction to concepts of validity, reliability and unbiasedness.

In this note, a coin tossing experiment which leads to three discrete distributions is discussed.