Resource Library

Students explore the definition and interpretations of the probability of an event by investigating the long run proportion of times a sum of 8 is obtained when two balanced dice are rolled repeatedly. Making use of hand calculations, computer simulations, and descriptive techniques, students encounter the laws of large numbers in a familiar setting. By working through the exercises, students will gain a deeper understanding of the qualitative and quantitative relationships between theoretical probability and long run relative frequency. Particularly, students investigate the proximity of the relative frequency of an event to its probability and conclude, from data, the order on which the dispersion of the relative frequency diminishes. Key words: probability, law of large numbers, simulation, estimation

Includes project file for Minitab and coding for a dice rolling simulation.

Poses the following problem: Suppose there was one of six prizes inside your favorite box of cereal. Perhaps it's a pen, a plastic movie character, or a picture card. How many boxes of cereal would you expect to have to buy, to get all six prizes?

StatKey is the analysis package to accompany the textbook "Statistics: Unlocking the Power of Data." StatKey includes interactive applets to describe and graph data, engage in bootstrapping and randomization tests, and explore sampling distributions and theoretical distributions.

May 8, 2007 webinar resented by Bill Notz, The Ohio State University, and hosed by Jackie Miller, The Ohio State University. In this webinar Bill Notz, the Editor of the Journal of Statistics Education (JSE), discusses all aspects of the journal. He outlines the mission and history of the JSE, describes the various departments of the journal, explains what you can find at the journal's web site, indicates the types of manuscripts the journal seeks to publish, and mentions possible future directions.

June 12, 2007 webinar presented by Rob Carver, Stonehill College, and hosted by Jackie Miller, The Ohio Sate University. We've probably all observed that some of our students become positively irritated with the uncertainty that remains after solving a problem of statistical inference. This webinar reports on a continuing empirical investigation of the relationship between Ambiguity Tolerance (AT) and students' facility in developing the skills of inferential reasoning. This research uses some validated measures of AT and of statistical thinking to focus on ambiguity tolerance as an explanatory or moderating factor in learning to apply the techniques of inference.

September 11, 2007 Teaching & Learning webinar presented by Ginger Rowell, Middle Tennessee State University, and hosted by Jackie Miller, The Ohio State University. The Internet is a great source of learning resources to help statistics teachers and students. Examples include interactive applets, videos, tutorials, lesson plans, case studies, and engaging learning activities. This webinar demonstrates how to assess statistics education learning materials based on the peer-review criteria used by digital libraries such as MERLOT and CAUSEweb.

September 9, 2008 Teaching and Learning webinar presented by Joan Garfield and Michelle Everson, University of Minnesota and hosted by Jackie Miller, The Ohio State University. This webinar discusses issues and challenges in preparing teachers of statistics at the secondary and college level. It then provides a case study of a graduate level course taught at the University of Minnesota that focuses on developing excellent teachers of statistics. The course is based on the GAISE guidelines and helps the students develop both knowledge of teaching (pedagogical knowledge) and specific knowledge about teaching statistics (pedagogical content knowledge). Topics, readings, activities, assessments, and discussions are described. In addition, the webinar discusses how the course was transformed from a face-to-face setting to an online environment.

March 11, 2008 Teaching and Learning webinar presented by Deborah Nolan, University of California at Berkeley and hosted by Jackie Miller, The Ohio State University. Computing is an increasingly important element of statistical practice and research. It is an essential tool in our daily work, it shapes the way we think about statistics, and broadens our concept of statistical science. Although many agree that there should be more computing in the statistics curriculum and that statistics students need to be more computationally capable and literate, it can be difficult to determine how the curriculum should change because computing has many dimensions. In this webinar Dr. Nolan explores alternatives to teaching statistics that include innovations in data technologies, modern statistical methods, and a variety of computing skills that will enable our students to become active and engaged participants in scientific discovery.

August 14, 2007 Teaching & Learning webinar presented by Oded Meyer, Carnegie Mellon University, and hosted by Jackie Miller, The Ohio State University. Carnegie Mellon University was funded to develop a "stand-alone" web-based introductory statistics course, and for several semesters they studied different ways in which the course could be used to support instruction. In this presentation, Dr. Meyer discusses some of the challenges in developing such a learning environment and ways in which the course tries to address them, as well as describing the design and results of accompanying studies.

October 9, 2007 Teaching & Learning webinar presented by Norean Sharpe, Babson College, and hosted by Jackie Miller, The Ohio State University. Writing can be a wonderful tool to help illuminate what students are learning in our statistics courses. Examples and strategies to include writing in your teaching toolkit -- and to increase the writing skills of students -- include team assignments, weekly case reports, in-class questions, and others. This webinar shares effective approaches and assignments gleaned from twenty years of experience using writing in introductory and upper-level statistics courses.