Reference Material

  • A statistician who works as a consultant shares information about his career and how he has learned to be more effective in the professional world in this September 2009 article in AMSTAT News.
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  • Many great resources are provided here for those seeking more information about a career in statistics.

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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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  • Statistics are to baseball what a flaky crust is to Mom's apple pie. is a quote by American television journalist Harry Reasoner (1923 - 1991). The quote was said in a story on the news magazine show, "60 minutes."
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  • I can prove anything by statistics except the truth is a quote by British politician George Canning (1770 - 1827). The quote is found on page 587 of the 1908 book "Dictionary of Thoughts" edited by Tryon Edwards. The quote may be used to illustrate the idea that statistical inference is often geared toward demonstrating what is unlikely to be true rather than proving what is true.
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  • February 9, 2010 T&L webinar presented by Hollylynne Lee (North Carolina State University) and Todd Lee (Elon University), and hosted by Jackie Miller (The Ohio State University). A model for probabilistic reasoning will be discussed that may support students' statistical reasoning. The development of the model and instructional implications are based on theoretical considerations and empirical results from work with middle grades students. Significant time for discussion is planned to get reactions to the model as well as to discuss aspects of probability that participants believe are foundational to building statistical literacy or reasoning.
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  • The AIMS project developed lesson plans and activities based on innovative materials that have been produced in the past few years for introductory statistics courses. These lesson plans and student activity guides were developed to help transform an introductory statistics course into one that is aligned with the Guidelines for Assessment and Instruction in Statistics Education (GAISE) for teaching introductory statistics courses. The lessons build on implications from educational research and also involve students in small and large group discussion, computer explorations, and hands-on activities.
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  • Probability is a 2 minute 14 second video that can be used in discussing the probability of rare events (e.g. how many consecutive times must a coin land heads before you question whether it is a fair coin?). The video was written, shot, and edited by Sam Rapien in 2007. The music is by Brett Musil and Sam Rapien and the single cast member is Jon Anderson. Mr. Rapien made this video while a graduate student in the Department of Art and Art History at the University of Nebraska, Lincoln.

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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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  • This online resource is intended to help students understand concepts from probability and statistics and covers many topics from introductory to advanced. You can follow the progression of the text, or you can click on a topic on the left. Key Words: Alpha Reliability; Analysis of Covariance (ANCOVA); Analysis of Variance (ANOVA); Bayesian Analysis; Bias; Binomial regression; Bonferroni adjustment; Bootstrapping; Categorical modeling; Central limit theorem; Chi-squared test; Clinical significance; Cluster analysis; Coefficient of variation; Confidence Intervals; Contingency Table; Controlled trial; Confounders; Correlation; Dimension reduction; Discriminant function analysis; Frequency; Normal; Poisson; Probability Distribution; Effect; Error; Factor Analysis; Goodness of Fit; Heteroscedasticity; Hypothesis Testing; Independence, Interactions; Kappa Coefficient; Latin Squares; Least Squares Means; Likert scales; Linear Regression; Logistic Regression; Multivariate ANOVA (MANOVA); Mixed Modeling; Multiple Linear Regression; Nonparametric models; Odds ratio; P Values; Path Analysis; Percentiles; Polynomial Regression; Power; PRESS; Probability; Relative Frequency; Repeated Measures; Sample Size; Sampling; Sensitivity; Stepwise regression; Structural equation modeling; T Test; Transformation; Validity.
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