Resource Library

November 23, 2010 Activity Webinar presented by Stacey Hancock, Reed College, Jennifer Noll, Portland State University, Sean Simpson, Westchester Community College, and Aaron Weinberg, Ithaca College, and hosted by Leigh Slauson, Capital University. Extra materials available for download free of charge. Many instructors ask students to demonstrate the frequentist notion of probability using a simulation early in an intro stats course. Typically, the simulation involves dice or coins, which give equal (and known) probabilities. How about a simulation involving an unknown probability? This webinar discusses an experiment involving rolling (unbalanced) pigs. Since the probabilities are not equal, this experiment also allows the instructor to have students think about the concept of fairness within games.

October 10, 2006 webinar presented By John Holcomb, Cleveland State University, and hosted by Jackie Miller, The Ohio State University. This webinar presents a quick overview of assessment methods related to student writing assignments and data analysis projects. Beginning with short writing assignments, Dr. Holcomb progresses through a range of different approaches to projects at the introductory course level. On-line resources containing existing project ideas will be shown along with ideas for creating one's own projects. The webinar also discusses several approaches to evaluating the range of assignments.

Many introductory Statistics courses consist of two main components: lecture sections and computer laboratory sections. In the computer labs, students often review fundamental course concepts, learn to analyze data using statistical software, and practice applying their knowledge to real world scenarios. Lab time could be better utilized if students arrived with 1) prior exposure to the core statistical ideas, and 2) a basic familiarity with the statistical software package. To achieve these objectives, PreLabs have been integrated into an introductory statistics course. A simple screen capture software (Jing) was used to create videos. The videos and a very short corresponding assignment together form a PreLab and are made available to students to access at appropriate times in the course. Some PreLabs were created to expose the students to statistical software details. Other PreLabs incorporate an available online learning resource or applet which allows students to gain a deeper understanding of a course concept through simulation and visualization. Not all on-line learning resources are ready to use 'as in' in a course. Some may be lacking a preface or description on how they are to be used; others may use slightly different notation or language than your students are accustomed to; a few may even contain an error or item that needs some clarification. One solution to such difficulties was to create a video wrapper so students can see how the applet works while receiving guidance from the instructor. In this webinar we will share the success story of how one introductory Statistics course integrated these video wrappers into the course and the discuss other possible applications.

January 26, 2010 webinar presented by Alicia Gram, Smith College, and hosted by Leigh Slauson, Capital University. This webinar describes an activity that uses data collected from an experiment looking at the relationship between two categorical variables: whether a cotton plant was exposed to spider mites; and did the plant contract Wilt disease? The activity uses randomization to explore whether there is a difference between the occurrence of the disease with and without the mites. The webinar includes a discussion of the learning goals of the activity, followed by an implementation of the activity then suggestions for assessment. The implementation first uses a physical simulation, then a simulation using technology. (Extra materials, including Fathom instructions for the simulation, available for download free of charge).

A game to aid in teaching experimental design and significance testing (especially one sample, two sample, and matched pair situations). Tangrams are puzzles in which a person is expected to place geometrically shaped pieces into a particular design. The on-line Tangram Game provides students the opportunity to design many versions of the original game in order to test which variables have the largest effect on game completion time. A full set of student and instructor materials are available and were created by Kevin Comiskey (West Point), Rod Sturdivant (Ohio State University) and Shonda Kuiper (Grinnell College) as part of the Stat2Labs collection.

This is my take on the ubiquitous M&Ms counting activity. Each student records the color proportions in a fun-size bag of M&Ms. We pool the class data and run a Chi-Square goodness-of-fit test to determine whether or not the color proportions match those claimed on the manufacturer's website. We consistently find that the proportions do not match. The blue M&Ms, in particular, are underrepresented. This activity also includes a review of the 1-proportion z confidence interval.

This activity 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.

This program has been written to explore the relationship between the data points and the error surface of the regression problem. On one hand you can learn how to represent a line in two different spaces ({x,y} and {k,d}), and on the other hand you see that solving the regression problem is nothing else than finding the minimum in the error surface.

This program visualizes the effects of outliers to regression lines. The user may pick up a point with the mouse and move it across the chart. The resulting regression line is automatically adjusted after each movement, showing the effect in an immediate and impressive way. The program Leverage allows one to experiment with the leverage effect. You can create a random sample of data noisy points on a line. Dragging one of the points away from the regression line immediately shows the effect, as the regression line is recalculated and moves according to the current data set. Not online: user has to download the program.

How can we accurately model the unpredictable world around us? How can we reason precisely about randomness? This course will guide you through the most important and enjoyable ideas in probability to help you cultivate a more quantitative worldview.

By the end of this course, you’ll master the fundamentals of probability and random variables, and you’ll apply them to a wide array of problems, from games and sports to economics and science.  This course includes 62 interactive quizzes and more than 400 probabilty-based problems with solutions.  Access to this course requires users to sign up for a free account.