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  • Song about the use of the Mann-Whitney U statistic (also known as the two sample Wilcoxon statistic). May be sung to the tune of "I Will Find You" by Peter Hammill; Fie Records, 1991. The audio was produced by Nicolas Acedo and sung by Jorge Baylon, both students in the University of Texas at El Paso Commercial Music Program.

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  • A song describing how sample means will follow the normal curve regardless of how skewed the population histogram is, provided n is very large.  The lyrics were written by Dennis Pearl and Peter Sprangers, both then at The Ohio State University.  The audio recording was produced by The University of Texas at El Paso student Nicolas Acedo who also performed the vocals

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  • A cartoon that can be used in teaching about the efficiency of using simulation in statistics. Cartoon 2006 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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  • A joke to be used in discussing the Sign test (based on whether an observation is above or below a specific value) and the Wilcoxon test (based on ordering the observations).  The joke was written by Larry Lesser from The University of Texas at El Paso in December 2020.

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  • A pun to start a discussion of the use of a sign test.  The joke was written by Dennis Pearl from Penn State University in 2020.

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  • "The purpose of this electronic service is to provide access to a collection of datasets suitable for teaching statistics. The datasets are stored either locally or on other computers throughout the world. The datasets have been organized by statistical technique to make it easier for you to find a dataset appropriate for your pedagogical needs. When a dataset is appropriate for several statistical techniques, it will appear under several categories. Each dataset consists of three files: one is a description of the data; the others are an ascii (text) file of the data and an Excel file of the data."
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  • This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: linear association, correlation coefficient, ridits/modified ridits, nonparametric methods, Cochran-Armitage Trend test, 

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  • This chapter discusses a collection of tests called distribution-free tests, or nonparametric tests, that do not make any assumptions about the distribution from which the numbers were sampled. The main advantage of distribution-free tests is that they provide more power than traditional tests when the samples are from highly-skewed distributions. 

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  • This site offers separate webpages about statistical topics relevant to those studying psychology such as research design, representing data with graphs, hypothesis testing, and many more elementary statistics concepts.  Homework problems are provided for each section.

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  • The goal of this text is to provide a broad set of topics and methods that will give students a solid foundation in understanding how to make decisions with data. This text presents workbook-style, project-based material that emphasizes real world applications and conceptual understanding. Each chapter contains:

    • An introductory case study focusing on a particular statistical method in order to encourage students to experience data analysis as it is actually practiced.
    • guided research project that walks students through the entire process of data analysis, reinforcing statistical thinking and conceptual understanding.
    • Optional extended activities that provide more in-depth coverage in diverse contexts and theoretical backgrounds. These sections are particularly useful for more advanced courses that discuss the material in more detail. Some Advanced Lab sections that require a stronger background in mathematics are clearly marked throughout the text.
    • Data sets from multiple disciplines and software instructions for Minitab and R.

    The text is highly adaptable in that the various chapters/parts can be taken out of order or even skipped to customize the course to your audience. Depending on the level of in-class active learning, group work, and discussion that you prefer in your course, some of this work might occur during class time and some outside of class. 

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