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  • This web-based package does a very complete range of statistical calculations designed to be user friendly. Formerly known as WebStat, it provides statistical calculation functions that would be done in most introductory statistics courses. Notable examples include being able to create histograms, pie charts and boxplots, calculation of summary statistics and confidence intervals, and performing hypothesis tests. It allows data to be entered in a spreadsheet style data window or opened from a file. Cost for students and professionals is $13 for 6 months and $23 for 12 months (instructors have complimentary access), and it does require a login. Key Word: Calculator.

     

    Stat Crunch's Available Features:  https://www.statcrunch.com/assets/documents/StatCrunch%20Statistical%20Procedures.pdf 

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  • A joke to use in talking about how simulation might aid in learning statistical inference.  The joke was written in April 2018 by Dennis Pearl from Penn State University with editorial help from Larry Lesser from University of Texas at El Paso.

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  • May 8, 2007 webinar resented by Bill Notz, The Ohio State University, and hosed by Jackie Miller, The Ohio State University. In this webinar Bill Notz, the Editor of the Journal of Statistics Education (JSE), discusses all aspects of the journal. He outlines the mission and history of the JSE, describes the various departments of the journal, explains what you can find at the journal's web site, indicates the types of manuscripts the journal seeks to publish, and mentions possible future directions.

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  • June 12, 2007 webinar presented by Rob Carver, Stonehill College, and hosted by Jackie Miller, The Ohio Sate University. We've probably all observed that some of our students become positively irritated with the uncertainty that remains after solving a problem of statistical inference. This webinar reports on a continuing empirical investigation of the relationship between Ambiguity Tolerance (AT) and students' facility in developing the skills of inferential reasoning. This research uses some validated measures of AT and of statistical thinking to focus on ambiguity tolerance as an explanatory or moderating factor in learning to apply the techniques of inference.

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  • September 11, 2007 Teaching & Learning webinar presented by Ginger Rowell, Middle Tennessee State University, and hosted by Jackie Miller, The Ohio State University. The Internet is a great source of learning resources to help statistics teachers and students. Examples include interactive applets, videos, tutorials, lesson plans, case studies, and engaging learning activities. This webinar demonstrates how to assess statistics education learning materials based on the peer-review criteria used by digital libraries such as MERLOT and CAUSEweb.

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  • TeachingWithData.org is portal of teaching and learning resources for infusing quantitative literacy into the social science curriculum. A Pathway of the National Science Digital Library, TwD aims to support the social science instructor at secondary and post-secondary schools by presenting user-friendly, data-driven student exercises, pedagogical literature, and much more! Resources are available on a wide range of topics and disciplines.

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  • The ASA Career Center serves as the main clearinghouse for information about jobs, careers, and employment for the statistical profession.

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  • This resource gives 3 questions readers should ask when presented with data and why to ask them: Where did the data come from? Have the data been peer-reviewed? How were the data collected? This page also describes why readers should: be skeptical when dealing with comparisons, and be aware of numbers taken out of context.

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  • September 9, 2008 Teaching and Learning webinar presented by Joan Garfield and Michelle Everson, University of Minnesota and hosted by Jackie Miller, The Ohio State University. This webinar discusses issues and challenges in preparing teachers of statistics at the secondary and college level. It then provides a case study of a graduate level course taught at the University of Minnesota that focuses on developing excellent teachers of statistics. The course is based on the GAISE guidelines and helps the students develop both knowledge of teaching (pedagogical knowledge) and specific knowledge about teaching statistics (pedagogical content knowledge). Topics, readings, activities, assessments, and discussions are described. In addition, the webinar discusses how the course was transformed from a face-to-face setting to an online environment.

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  • March 11, 2008 Teaching and Learning webinar presented by Deborah Nolan, University of California at Berkeley and hosted by Jackie Miller, The Ohio State University. Computing is an increasingly important element of statistical practice and research. It is an essential tool in our daily work, it shapes the way we think about statistics, and broadens our concept of statistical science. Although many agree that there should be more computing in the statistics curriculum and that statistics students need to be more computationally capable and literate, it can be difficult to determine how the curriculum should change because computing has many dimensions. In this webinar Dr. Nolan explores alternatives to teaching statistics that include innovations in data technologies, modern statistical methods, and a variety of computing skills that will enable our students to become active and engaged participants in scientific discovery.

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