Graphical Paradigms for Teaching and Using Statistics

学生们首先通过柱状图和直方图等简单图形学习统计思维。在大学阶段，统计数据的图形化方法较少使用。这在一定程度上是因为优秀的图形才刚刚出现在计算机上。可能更重要的原因是，虽然数值方法有坚实的数学基础，但图形统计主要由绘图方法组成，没有伴随的理论。在这项研究中，该项目正在开发一种理论上合理的回归分析图形方法，这是旨在了解一个变量如何依赖于其他变量的统计技术的集合。这个项目与其他图形项目的不同之处在于，它发展了一种统一的理论，使图形更容易理解，在数据分析中也更有用。该项目正在制作独立的教学材料、教科书和教师辅助工具，并为大学教师举办如何使用这些材料的讲习班。

Students first learn statistical thinking through simple graphics like bar charts and histograms. At the college level, a graphical approach to statistics is less often used. This is so in part because good graphics have only just become available on computers. Possibly a more important reason is that while numerical methods have a firm mathematical footing, graphical statistics have consisted primarily of methods of graphing, without accompanying theory. In this research, the project is developing a theoretically sound graphical approach to regression analysis, which is the collection of statistical techniques designed to understand how one variable depends on others. What differentiates this project from others on graphics is the development of a unified theory to make graphs more comprehensible, and much more useful in the analysis of data. The project is producing self-contained teaching materials, textbooks and teacher's aids, and presenting workshops for college teachers on how to use this material.