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  • This issue contains articles about binomial confidence intervals; the team effect in stock car racing; using multiple tests (one-sample t-test and sign test); the "two-envelope exchange paradox" (similar to the Monty Hall problem) with discussions of expectation, likelihood, and inference; regression line vs. trend line; calculations of standard normal table values and pi; teaching at a small liberal arts college; modeling extreme events.
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  • This issue contains articles about steroids in baseball; finding ways to make learning statistics fun; an interview with Joan Garfield about Statistics Education; an introduction to response surface methodology; and a look at the vocabulary used in experimental design.
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  • This issue contains articles about Karl Pearson (150 years after his birth); finding more ways to make learning statistics fun; simulating capture-recapture sampling in Excel and by hand; common misconceptions in statistics; a correlation-based puzzler and a STATäó¢DOKU puzzle.
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  • This site includes several short tutorials that showcase different features of JMP 7. There is also another site with JMP tutorials at http://stat.fsu.edu/tutorials/
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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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  • October 26, 2010 Activity Webinar presented by Tisha Hooks, Winona State University and hosted by Leigh Slauson, Capital University. Extra materials available to download free of charge. The purpose of this webinar is to introduce an activity to enhance students' understanding of various descriptive measures. In particular, by completing this hands-on activity students will experience a visual interpretation of a mean, median, outlier, and the concept of distance-to-mean.
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  • September 28, 2010 Activity webinar presented by Carolyn Cuff, Westminster College and hosted by Leigh Slauson, Capital University. Extra materials available for download free of charge. Students must confront their misconceptions before we can teach them new concepts. Naively, a census is an accurate method to quantify a population parameter. A very brief, memorable and easy to implement activity demonstrates that a census is at best difficult even for a small and easily enumerated population.
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  • August 24, 2010 Activity Webinar presented by Jackie Miller, The Ohio State University and hosted by Leigh Slauson, Capital University. Extra materials available for download free of charge. When Dr. Miller took a graduate course in College Teaching, she learned the jigsaw method. The jigsaw is a cooperative learning technique where students work together in a "home" group on a specific task and then are placed into "jigsaw" groups made up of one member from each home group. For example, if there are 25 students in the class, 5 students would be assigned to each of the A, B, C, D, E home groups, and each jigsaw group would each one member from A, B, C, D, and E. While in the jigsaw groups, the students teach each other what they learned in their home groups. Dr. Miller recalls bringing the idea back with her to one of the OSU elementary statistics courses where it has been used successfully since 1996. Recently a graduate teaching assistant (GTA) suggested to other GTAs that this might be good in another introductory statistics course, and the activity has been adopted successfully . As structured, the jigsaw can be used in an exam review in statistics by assigning students to, say, 5 exercises that they need to master before they go to their jigsaw groups to teach others about their exercise. During this webinar, the webinar presents how the jigsaw is done and address questions like: How do you budget your time for this class activity? How do you know that students are teaching the correct answer? How do you know that students are not just furiously writing down answers instead of listening to understand the concept? Can this work for you? By the end of the webinar, hopefully you will be as intrigued as Dr. Miller was to learn about the jigsaw method and will want to try it in your classroom.
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  • July 27, 2010 Activity Webinar presented by Herle McGowan, North Carolina State University and hosted by Leigh Slauson, Capital University. Extra materials available for download free of charge. In this webinar, the webinar discusses the end-of-semester project that is used in North Carolina State's introductory statistics course. This project supports statistical thinking by allowing students to apply knowledge accumulated throughout the semester. Students are presented with a research question and must design and carry out an experiment, analyze the resulting data and form a conclusion over the course of several class periods.
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  • July 13, 2010 T&L webinar presented by Webster West (Texas A&M University) and hosted by Jackie Miller(The Ohio State University). In introductory statistics courses, web-based applets are often used to visually conduct large simulation studies illustrating statistical concepts. However, it is difficult to determine what (if anything) students learn from repeatedly pressing a button when using applets. More advanced options such as writing/running computer code are typically considered to be much too advanced for most introductory courses. The web-based software package, StatCrunch, now offers simulation capabilities that strike a middle ground between these two extremes. The instructor/student needs only to perform a small number of steps using the menu driven interface with each step being key to understanding the underlying data structure. This talk will cover the steps required to study concepts such as the central limit theorem, confidence intervals, hypothesis testing and regression using StatCrunch.
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