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  • A statistical analysis, properly conducted, is a delicate dissection of uncertainties, a surgery of suppositions. is a quote from Statistician Michael J. Moroney (1940 - ). The quote appears in his 1951 book "Facts from Figures".
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  • This is a song suitable for middle school level statistics in reinforcing key elements of the scientific method. College-level use might include playing before a lecture to lighten the mood while setting up. The song's lyrics and music were composed by Jeff Hall audio file is a performance by the scientific jam band (see www.scientificjam.com/scijam2.htm)
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  • Indeed, the laws of chance are just as necessary as the causal laws themselves. is a quote of quantum physicist David J. Bohm (1917- 1992). The quote appears on page 23 of his 1957 book "Causality and Chance in Modern Physics". The quote also appears in "Statistically Speaking: A dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither.
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  • Everyone believes in the normal law, the experimenters because they imagine that it is a mathematical theorem, and the mathematicians because they think it is an experimental fact. is a quote by French physicist Jonas Ferdinand Gabriel Lippmann (1945-1921). The quote may used in a class discussion of the assumption of normality. It can be found in Henri Poincare's 1896 book "Calcul de Probabilities" (in French).
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  • No matter how much reverence is paid to anything purporting to be statistics," the term has no meaning unless the source, relevance, and truth are all checked." is a quote by American English professor Tom B. Burnam (1913-1991). The quote is found on page 244 of his 1975 book "The Dictionary of Misinformation".
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  • There is no free hunch. is quote by American psychologist and political scientist Robert P. Abelson (1928 - 2005). The quote is found on page 142 of his 1995 book "Statistics as a Principled Argument". It is referred to as "Abelson's Sixth Law" in a discussion of the generalizability of estimated effects.
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  • A cartoon for use in discussing outliers. The cartoon is by New Zealand cartoonist Nick Kim (see www.lab-initio.com). This copyrighted cartoon is available for free use in classes and on course webistes at non-profit educational institutions. Commercial inquiries should be directed to the artist (e-mail:nick@lab-initio.com).
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  • A cartoon to use in discussing the importance of indicating the variability associated with any prediction. The cartoon is the work of Theresa McCracken and appears as #5756 on McHumor.com (appearing here with a statistics-based caption change suggested by Dennis Pearl). Free for non-profit use in statistics course such as in lectures and course websites.
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  • August 10, 2010 T&L webinar presented by Diane Fisher (University of Louisiana at Lafayette), Jennifer Kaplan (Michigan State University), and Neal Rogness (Grand Valley State University) and hosted by Jackie Miller(The Ohio State University). Our research shows that half of the students entering a statistics course use the word random colloquially to mean, "haphazard" or "out of the ordinary." Another large subset of students define random as, "selecting without prior knowledge or criteria." At the end of the semester, only 8% of students we studied gave a correct statistical definition for the word random and most students still define random as, "selecting without order or reason." In this session we will present a classroom approach to help students better understand what statisticians mean by random or randomness as well as preliminary results of the affect of this approach.
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  • September 14, 2010 T&L webinar presented by Thomas Moore(Grinnell College) and hosted by Jackie Miller(The Ohio State University). Permutation tests and randomization tests were introduced almost a century ago, well before inexpensive, high-speed computing made them feasible to use. Fisher and Pitman showed the two-sample t-test could approximate the permutation test in a two independent groups experiment. Today many statistics educators are returning to the permutation test as a more intuitive way to teach hypothesis testing. In this presentation, I will show an interesting teaching example about primate behavior that illustrates how simple permutation tests are to use, even with a messier data set that admits of no obvious and easy-to-compute approximation.
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