Resource Library

July 28, 2009 Activity webinar presented by Jo Hardin, Pomona College, and hosted by Leigh Slauson, Otterbein College. Based on an activity by John Spurrier, this webinar uses a baseball example to introduce students to Bayesian estimation. Students use prior information to determine prior distributions which lead to different estimators of the probability of a hit in baseball. The webinar also compares different Bayesian estimators and different frequentist estimators using bias, variability, and mean squared error. The effect that sample size and dispersion of the prior distribution have on the estimator is then illustrated by the activity.

Webinar recorded May 9, 2006 presented by Carl Lee of Central Michigan University and hosted by Jackie Miller of The Ohio State University. Do you use hands-on activities in your class? Would you be interested in using data collected by students from different classes at different institutions? Would you be interested in sharing your students' data with others? Does it take more time than you would like to spend in your class for hands-on activities? Do you have to enter the hands-on activity data yourself after the class period? If your answer to any of the above questions is "YES", then, this Real-Time Online Database approach should be beneficial to your class. In this presentation, Dr. Lee (1) introduces the real-time online database (stat.cst.cmich.edu/statact) funded by a NSF/CCL grant, (2) demonstrates how to use the real-time database to teach introductory statistics using two of the real-time activities and (3) shares with you some of the assessment activities including activity work sheets and projects.

The AIMS project developed lesson plans and activities based on innovative materials that have been produced in the past few years for introductory statistics courses. These lesson plans and student activity guides were developed to help transform an introductory statistics course into one that is aligned with the Guidelines for Assessment and Instruction in Statistics Education (GAISE) for teaching introductory statistics courses. The lessons build on implications from educational research and also involve students in small and large group discussion, computer explorations, and hands-on activities.

A cartoon that might be used in introducing scatterplots and correlation. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.

Meditation on Statistical Method is a poem by American poet and Brandeis University professor James Vincent Cunningham (1911 - 1985). The poem was originally published in "The Exclusions of a Rhyme: Poems and Epigrams" (1960; Swallow Press) and may also be found in "The collected poems and epigrams of J.V. Cunningham" (1971; Swallow Press).

This limerick was written by Columbia University professor of biostatistics, Joseph L. Fleiss (1938 -2003). It was published along with three other limericks by Dr. Fleiss in a letter to the editor of "The American Statistician" (volume 2; 1967, page 49). It was written while he worked as a biostatistician at the Department of Mental Hygiene of the State of New York just prior to receiving his Ph.D. and joining the faculty at Columbia.

A series of 19 songs used to teach Structural Equations Modeling (SEM) by Alan Reifman of Texas Tech University. A video of an in-class performance of the musical on April 27, 2007, is also available at the website. The Musical took second place in the 2007 A-Mu-sing competition.

This pdf text file gives a short introduction to the methods of Bayesian inference. It gives a simple example that deals with jumping a paper frog. The topics listed in this document include: An example, comparison of frequentist and Bayesian methods, credible vs. confidence intervals, choice of prior and its effect on the posterior distribution.

This activity is an example of Cooperative Learning in Statistics. It uses student's own data to introduce bivariate relationship using hand size to predict height. Students enter their data through a real-time online database. Data from different classes are stored and accumulated in the database. This real-time database approach speeds up the data gathering process and shifts the data entry and cleansing from instructor to engaging students in the process of data production. Key words: Regression, correlation data collection, body measurements

This activity makes use of a campus-based resource to develop a "capstone" project for a survey sampling course. Students work in small groups and use a complex sampling design to estimate the number of new books in the university library given a budget for data collection. They will conduct a pilot study using some of their budget, receive feedback from the instructor, then complete data collection and write a final report.