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  • It is better to be satisfied with probabilities than to demand impossibilities and starve. A quote attributed to German philosopher, poet, and dramatist Friedrich Schiller (1759 - 1805). The quote may also be found in "The New Book of Unusual Quotations" by Rudolf Flesch (Harper & Row, 1966)
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  • A joke about the economic value of a degree in the applied mathematical sciences compared to a more theoretical degree.
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  • There is no alchemy of probabilities that will change ignorance into knowledge. A quote by American psychologist Edwin G. Boring found in "The logic of the Normal Law of error in mental measurement" published in "The American Journal of Psychology" page 1, volume 31, 1920.
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  • 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.
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  • A cartoon that might be used in introducing scatterplots and correlation. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.
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  • A cartoon to teach about the need for statistical techniques in drawing out the salient features in massive data sets. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.
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  • A cartoon to teach about the interpretation of confidence statements. The cartoon plays on the idea of what would happen if the same process was repeated over-and-over again. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.
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  • This activity begins with an instructor demonstration followed by a student out-of-class assignment. Students will observe their instructor create a scatterplot and observe how the correlation coefficient changes when outlier points are added. Students are then given a follow up assignment, which guides them through the applet. In addition, the assignment provides insight about outliers and their effect on correlation. This activity will show exactly how outliers numerically change the correlation coefficient value and to what degree.
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  • This visualization activity combines student data collection with the use of an applet to enhance the understanding of the distributions of slope and intercept in simple linear regression models. The applet simulates a linear regression plot and the corresponding intercept and slope histograms. The program allows the user to change settings such as slope, standard deviation, sample size, and more. Students will then see theoretical distributions of the slope and intercept and how they compare to the histograms generated by the simulated linear regression lines.
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  • This in-class demonstration combines real world data collection with the use of the applet to enhance the understanding of sampling distribution. Students will work in groups to determine the average date of their 30 coins. In turn, they will report their mean to the instructor, who will record these. The instructor can then create a histogram based on their sample means and explain that they have created a sampling distribution. Afterwards, the applet can be used to demonstrate properties of the sampling distribution. The idea here is that students will remember what they physically did to create the histogram and, therefore, have a better understanding of sampling distributions.
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