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  • 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.

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  • This simulation illustrates least squares regression and how the least squares solution minimizes the sum of the squared residuals. The applet demonstrates, in a visual manner, various concepts related to least squares regression. These include residuals, sum of squares, the mean line, how the line of best fit is determined, and how the line of least squares solution minimizes the sum of the squared residuals.

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  • This recording of a web seminar (webinar) provides a tour of StatCrunch. StatCrunch (www.statcrunch.com) is a Web-based data analysis package. StatCrunch has all of the routines required for introductory statistics and many more. The software also offers pedagogical features such as interactive graphics. Many of these capabilities are discussed and demonstrated by StatCrunch developer Webster West.

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  • This collection of YouTube videos is designed to teach individuals how to use StatCrunch to enter data, graph data, obtain descriptive statistics, and conduct many different kinds of statistical analyses.

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  • 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.

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  • A sketch by Anastasia Mandel reinterpreting Judith with the Head of Holofernes by Cristofano Allori (1615) with the statistical caption "Segmentation; this one even helped to disperse an army." This is part of a collection of sketches by Anastasia Mandel and their accompanying statistical captions discussed in the paper "How art helps to understand statistics" (Model Assisted Statistics and Applications, 2009) by Stan Lipovetsky and Igor Mandel in volume 4 pages 313-324. Free to use in classrooms and on course websites.

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  • Many of us, while teaching an introductory statistics course, have mentioned some of the history behind the methodology, perhaps just in passing. We might remark that an English chap by the name of R. A. Fisher is responsible for a great deal of the course content. We could further point out that the statistical techniques used in research today were developed within the last century, for the most part. At most, we might reveal the identity of the mysterious "Student" when introducing the t-test to our class. I propose that we do more of this. This webinar will highlight some opportunities to give brief history lessons while teaching an introductory statistics course.

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  • This 6 minute 39 second video can be used to teach the difference between correlation and causation. For example, that a relationship between X and Y might be explained by X causing Y, Y causing X, or a third factor that drives them both. The video is episode #109 (Nov 10, 2009) in the Psych Files podcast series produced and hosted by Michael A. Britt, Ph.D. at www.thepsychfiles.com. Video is free to use in the classroom or on course websites under a non-commercial ShareAlike creative commons license.

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  • This simulation allows you to roll two dice and compare empirical and probability histograms for the sum or product of the two outcomes.

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  • This applet performs the Student's t test on two sets of data, and reports the average and variance for both sets of data, the t score, degrees of freedom, and one and two tailed P values.

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