May 13, 2008 Teaching and Learning webinar presented by Joy Jordan, Lawrence University and hosted by Jackie Miller, The Ohio State University. Writing can be an effective instrument for students learning new concepts, and there is a plethora of writing-to-learn research. This Webinar summarizes important findings from the writing literature, as well as providing specific writing-assignment examples for the introductory statistics classroom.
July 8, 2008 Teaching and Learning webinar presented by Shonda Kuiper, Grinnell College and hosted by Jackie Miller, The Ohio State University. Many instructors use projects to ensure that students experience the challenge of synthesizing key elements learned throughout a course. However, students can often have difficulty adjusting from traditional homework to a true research project that requires searching the literature, transitioning from a research question to a statistical model, preparing a proposal for analysis, collecting data, determine an appropriate technique for analysis, and presenting the results. This webinar presents multi-day lab modules that bridge the gap between smaller, focused textbook problems to large projects that help students experience the role of a research scientist. These labs can be combined to form a second statistics course, individually incorporated into an introductory statistics course, used to form the basis of an individual research project, or used to help students and researchers in other disciplines better understand how statisticians approach data analysis.
February 10, 2009 Teaching and Learning webinar presented by Andrew Zieffler, Bob delMas, and Joan Garfield, University of Minnesota, and hosted by Jackie Miller, The Ohio State University. This webinar presents an overview of the materials and research-based pedagogical approach to helping students reason about important statistical concepts. The materials presented were developed by the NSF-funded AIMS (adapting and Implementing Innovative Materials in Statistics) project at the University of Minnesota (www.tc.umn.edu/~aims).
May 12, 2009 Teaching and Learning hour-long webinar panel discussion presented by Laura Kubatko, The Ohio State University; Danny Kaplan, Macalester College; and Jeff Knisley, East Tennessee State University, and hosted by Jackie Miller, The Ohio State University. National reports such as Bio2010 have called for drastic improvements in the quantitative education that biology students receive. The three panelists are involved in three differently structured integrative programs aimed to give biology students the statistics that are useful in learning and doing biology. The three programs have some surprising things in common for teaching introductory statistics. All three involve connecting calculus and statistics. All three reach beyond the mathematical topics usually encountered in intro statistics in important ways. All three aim to keep the mathematics and statistics strongly connected to biology. The panelists describe their different approaches to teaching statistics for biology and discuss how and why an integrated approach gives advantages. Important issues are how to tie statistics advantageously with calculus, how to keep "advanced" mathematical and statistical topics accessible to introductory-level biology students, and how to employ computation productively. The discussion contrasts a comprehensive "team" approach (at ETSU) with stand-alone courses (at Macalester and at OSU) and refers to the institutional opportunities and constraints that have shaped the programs at their different institutions.
This article from the September 2009 issue of AMSTAT News features Dr. Robert Starbuck telling the story of his journey to become a statistician.
This site provides general information to students considering majors in Statistics or Actuarial Science.
This site provides information for those considering careers as a statistician. The site delves into the nature of the work as a statistician, training, other qualifications, and advancement, employment opportunities, job outlook information, and projected earnings.
This simulation involves a series of balls passing through bins to eventually yield a normal distribution. Information is also provided about what the normal distribution is.
This page of Statistical Java describes 11 different probability distributions including the Binomial, Poisson, Negative Binomial, Geometric, T, Chi-squared, Gamma, Weibull, Log-Normal, Beta, and F. Each distribution has its own applet in which users can manipulate the parameters to see how the distribution changes. The parameters are described on the main page as well as situations that would use each distribution. The equations of the distributions are not given. To select between the different applets you can click on Statistical Theory, Probability Distributions and then the Main Page. At the bottom of this page you can make your applet selection. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/
A computational tool that runs the one-way ANOVA by the user inputing individual data or by copying and pasting a delimitted data set.