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Statistical Topic

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  • December 12, 2006 webinar presented by Michelle Everson, University of Minnesota, and hosted by Jackie Miller, The Ohio State University. This webinar focuses on describing an introductory statistics course that is taught completely online. The structure of this course is described, and samples of different student assignments and activities are presented. Assessment data and student feedback about the course are also presented. Discussion focuses on issues that must be considered when developing and administering an online course, such as the instructor's role in the online course and ways to create an active learning environment in an online course.

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  • March 13, 2007 webinar presented by Andrew Zieffler, University of Minnesota, and hosted by Jackie Miller, The Ohio State University. The interdisciplinary field of inquiry that is statistics education research spans a diverse set of disciplines and methodologies. A recent review of a subset of this literature, the research on teaching and learning statistics at the college level, was used to raise some practical issues and pose some challenges to the field of statistics education. These are addressed in this CAUSE webinar. In addition, a recent doctoral dissertation study is used to illustrate some of these challenges and offer suggestions for how to deal with them.

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  • In this 20 minute video, doctor and researcher Hans Rosling uses his fascinating data-bubble software to burst myths about the developing world. The video includes new analysis on China and the post-bailout world, mixed with classic data shows.

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  • In this short 3 minute video, mathematician and magician Arthur Benjamin offers a bold proposal on how to make math education relevant in the digital age.

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  • Many introductory Statistics courses consist of two main components: lecture sections and computer laboratory sections. In the computer labs, students often review fundamental course concepts, learn to analyze data using statistical software, and practice applying their knowledge to real world scenarios. Lab time could be better utilized if students arrived with 1) prior exposure to the core statistical ideas, and 2) a basic familiarity with the statistical software package. To achieve these objectives, PreLabs have been integrated into an introductory statistics course. A simple screen capture software (Jing) was used to create videos. The videos and a very short corresponding assignment together form a PreLab and are made available to students to access at appropriate times in the course. Some PreLabs were created to expose the students to statistical software details. Other PreLabs incorporate an available online learning resource or applet which allows students to gain a deeper understanding of a course concept through simulation and visualization. Not all on-line learning resources are ready to use 'as in' in a course. Some may be lacking a preface or description on how they are to be used; others may use slightly different notation or language than your students are accustomed to; a few may even contain an error or item that needs some clarification. One solution to such difficulties was to create a video wrapper so students can see how the applet works while receiving guidance from the instructor. In this webinar we will share the success story of how one introductory Statistics course integrated these video wrappers into the course and the discuss other possible applications.

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  • It's Just STATA Code To Me is a song written by Dorry Segev of Johns Hopkins University that reflects on a number of issues in biostatistical data analysis. The song may be sung to the tune of Billy Joel's 1980 hit song "It's Still Rock and Roll To Me." The lyrics were written for Marie DIener-West's Biostatistics 653 course at Johns Hopkins that regularly asks students to create songs, videos, and poetry with biostatistics themes.

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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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  • 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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  • The primary themes of this parody involve elementary probability and the importance of graphical summaries. It may be sung to the tune of "Big Yellow Taxi" by Canadian songwriter Joni Mitchell, 1970. Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.

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  • Song advocating a preference for Bayesian inferential procedures. May sing to the tune of Neil Diamond's 1966 song "I'm a Believer" made popular by the Monkees. Lyrics by Bradley Carlin (2002). Free to use for non-commercial educational purposes. Contact author to use in publications or for commercial purposes. Accompanying musical track was recorded Sunday September 16, 2002. The lyrics were written by Brad for the Valencia 7 conference, Tenerife, Spain, June 2002;and was first performed there by the Bayesian Band (Brad Carlin, Mark Glickman, and David Heckerman). The lyrics may be found in volume 37, issue 1 of "IMS Bulletin" and in the "Bayesian Songbook" (www.biostat.umn.edu/~brad/cabaret.html).

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