Resource Library

January 12, 2010 T&L webinar presented by Marsha Lovett (Carnegie Mellon University) and hosted by Jackie Miller (The Ohio State University). In Statistics as in many disciplines, students need to learn about complex concepts and dynamically changing processes. How can instructors help their students begin to "see" these complex topics the way experts do, and are there tools that can help? In this webinar, I will review key findings on how computer visualizations and simulations can best support student learning and then take those findings to generate effective strategies for teaching with simulations and visualizations.

June 22, 2010 Activity webinar presented by Paul Roback, St. Olaf College and hosted by Leigh Slauson, Capital University. This webinar describes an in-class activity, motivated by Case Study 1.1.1 in The Statistical Sleuth, in which students compose haiku poems about statistics. Their poems are used to introduce two-sample t-tests and randomization tests. In addition, the in-class experiment leads to good discussion about experimental design issues, where students compare our design to the actual experiment described in Amabile et al.(1985) "Motivation and Creativity: Effects of Motivational Orientation on Creative Writers", Journal of Personality and Social Psychology 48(2): 393-399. I use this activity on the first day of our second course in applied statistics (Statistical Modeling), but it could easily be used in an introductory course as well. Examples of haiku poems which have resulted from this activity can be found under CAUSEweb > Resources > Fun > Poem (direct link), or at www.causeweb.org/cwis/SPT--FullRecord.php?ResourceId=1883.

May 25, 2010 Activity webinar presented by Ivan Ramler, St. Lawrence University and hosted by Leigh Slauson, Capital University. This webinar discusses an undergraduate Mathematical Statistics course project based on the popular video game Guitar Hero. The project included: 1) developing an estimator to address the research objective "Are notes missed at random?", 2) learning bootstrapping techniques and R programming skills to conduct hypothesis tests and 3) evaluating the quality of the estimator(s) under certain sets of scenarios.

In this module, students can test their knowledge of levels of measurement by attempting to determine the the level of measurement of ten different variables. For each variable, a statement is also provided and students can indicate whether the statement about the variable is valid or invalid (given the way in which the variable was measured). There is also a brief "refresher" included here about levels of measurement.

A joke to teach the meaning of "significance" written in 2011 by University of Texas at El Paso professor of Mathematical Sciences, Lawrence Mark Lesser (1964-).

A collection of applets addressing data analysis, sampling distribution simulations, and probability and inference. Some can be used individually, though others require context from the textbook.

Here one finds a collection of applets and famous problems in probability (as well as other areas of mathematics such as calculus and geometry). Some of the topics/problems include: Bertrand's Paradox, Birthday Coincidence, Buffon's Needle (Noodle), Lewis Carroll's Problem, Monty Hall Dilemma, Parrondo Paradox, and Three pancakes problem.

A mathematical word processor that includes an easy-to-use computer algebra system (MuPad). Products include Scientific Wokplace, Scientific Word, Scientific Notebook, and MuPad Pro. Student version are available.

This random number generator produces a data table with up to 10 columns and up to 2500 rows. For random integers, users must specify the data range. For data from a Normal (Gaussian) distribution, users specify mean and standard deviation.

This online calculator allows users to enter 16 observations with up to 4 dependent variables and calculates the regression equation, the fitted values, R-Squared, the F-Statistic, mean, variance, first order serial-correlation, second order serial-correlation, the Durbin-Watson statistic, and the mean absolute errors. It also tests normality and gives the i-th residuals.