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Statistical Topic

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  • This activity focuses on basic ideas of linear regression. It covers creating scatterplots from data, describing the association between two variables, and correlation as a measure of linear association. After this activity students will have the knowledge to create output that yields R-square, the slope and intercept, as well as their interpretations. This activity also covers some of the basics about residual analysis and the fit of the linear regression model in certain settings. The corresponding data set for this activity, 'BAC data', can be found at the following web address: http://www.causeweb.org/repository/ACT/BAC.txt

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  • This activity explains the important features of a distribution: shape, center, spread, and unusual features. It also covers how to determine the difference between mean and median, and their respective measures of spread, as well as when to apply them to a particular distribution. Graphical displays such as: histograms and boxplots are also introduced in this activity. The corresponding data set for this activity is found at the following web address: http://www.causeweb.org/repository/ACT/food.txt

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  • 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.

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  • Webinar presented September 12, 2006 by Brian Jersky, St. Mary's College, and Robert Gould, UCLA, and hosted by Jackie Miller, The Ohio State University. This webinar discusses resources available to educators to assist them in crafting lesson plans that meet the GAISE. The presenters briefly explain the GAISE, which were endorsed by the American Statistical Association and also the National Council of Teachers of Mathematics, and demonstrate various resources offered through CAUSEweb and other channels.

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  • December 12, 2006 webinar presented by Michelle Everson, University of Minnesota, and hosted by Jackie Miller, The Ohio State University. This webinar focuses on describing an introductory statistics course that is taught completely online. The structure of this course is described, and samples of different student assignments and activities are presented. Assessment data and student feedback about the course are also presented. Discussion focuses on issues that must be considered when developing and administering an online course, such as the instructor's role in the online course and ways to create an active learning environment in an online course.

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  • In this 20 minute video, doctor and researcher Hans Rosling uses his fascinating data-bubble software to burst myths about the developing world. The video includes new analysis on China and the post-bailout world, mixed with classic data shows.

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  • 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).

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  • 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.

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  • 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.

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  • 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.

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