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  • Plot the theoretical p-value distribution and power curve for an independent t-test based on the effect size, sample size, and alpha.

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  • Explore the Vovk-Sellke Maximum p-Ratio, a measure that indicates the maximum diagnosticity of a given p-value. Choose your own p-value to find out how diagnostic it is for your research!

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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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  • As mentioned on the home page of this resource "This site presents workbook-style, project-based material that emphasizes real world applications and conceptual understanding. This material is designed to give students a sense of the importance and allure of statistics early in their college career. By incorporating many of the successful reforms of the introductory statistics course into a wide range of more advanced topics we hope that students in any discipline can realize the intellectual content and broad applicability of statistics."

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  • Correspondence analysis is a method allowing you to describe synthetically a contingency table in which homogeneous individuals are classified on two criterias (or categorical variables, continuous ones being usable if discretized).  This resource tells how it can be used, graphical representations of this process, and gives examples of it in action. 

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  • The Research Methods Knowledge Base is a comprehensive web-based textbook that addresses all of the topics in a typical introductory undergraduate or graduate course in social research methods.  It covers the entire research process including: formulating research questions; sampling (probability and nonprobability); measurement (surveys, scaling, qualitative, unobtrusive); research design (experimental and quasi-experimental); data analysis; and, writing the research paper.  It also addresses the major theoretical and philosophical underpinnings of research including: the idea of validity in research; reliability of measures; and ethics.  The Knowledge Base was designed to be different from the many typical commercially-available research methods texts.  It uses an informal, conversational style to engage both the newcomer and the more experienced student of research.  It is a fully hyperlinked text that can be integrated easily into an existing course structure or used as a sourcebook for the experienced researcher who simply wants to browse.

     

    Navigate this source:  http://www.socialresearchmethods.net/kb/contents.php  

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  • Statistics forum for questions/conversations ranging from homework problems in statistics and probability and help using statistical software to statistical research inquiries and career advising.

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  • Share with your students why the presence of an outlier affects which measure of central tendency to report. Feel free to modify this Powerpoint presentation to fit the needs of your students. Included at the end are additional online resources to further engage your students in their learning about the mean, median, and mode. The presentation is covered by a Creative Commons Attribution-Share Alike 3.0 License.

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  • This applet builds confidence intervals for the percentage of orange candies in box with two colors of candies. A smaller box visualizes the sample, and a graph keeps track of the location of the confidence interval. Students can take one sample (producing one CI) repeatedly, or take 100 random samples at once. The population percentage is hidden from view unless the student asks to see it, in which case it is displayed on the graph of confidence intervals. This allows the students to see whether each interval "hits" or "misses". Several parameters can be varied: sample size, confidence level and number of samples. A set of questions alongside the applet guides students.

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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 STAT.DOKU puzzle.

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